Reduction In Emission Intensity Research Articles

Factors Affecting Enteric Emission Methane and Predictive Models for Dairy Cows.

Enteric methane emission is the main source of greenhouse gas contribution from dairy cattle. Therefore, it is essential to evaluate drivers and develop more accurate predictive models for such emissions. In this study, we built a large and intercontinental experimental dataset to: (1) explain the effect of enteric methane emission yield (g methane/kg diet intake) and feed conversion (kg diet intake/kg milk yield) on enteric methane emission intensity (g methane/kg milk yield); (2) develop six models for predicting enteric methane emissions (g/cow/day) using animal, diet, and dry matter intake as inputs; and to (3) compare these 6 models with 43 models from the literature. Feed conversion contributed more to enteric methane emission (EME) intensity than EME yield. Increasing the milk yield reduced EME intensity, due more to feed conversion enhancement rather than EME yield. Our models predicted methane emissions better than most external models, with the exception of only two other models which had similar adequacy. Improved productivity of dairy cows reduces emission intensity by enhancing feed conversion. Improvement in feed conversion should be prioritized for reducing methane emissions in dairy cattle systems.

Effect of Fe2O3 Nanoparticles Dust on the D.C Plasma Characteristics with Mirror Magnetron

In this paper, the effect of iron oxide nanoparticles dust (Fe2O3 NPs) on the parameters of DC electric discharge plasma under vacuum in argon gas was studied with the presence of a mirror magnetron behind the electrodes (cathode and anode) at constant pressure and with different amounts of Fe2O3 nanoparticles. Calculations presented a reduction of the plasma emission intensity with the NPs content. Both the plasma density (calculated by Stark's broadening method) and the mean electron temperature (calculated using Boltzmann's equation) decreased with increasing the Fe2O3 nanoparticles dust content, which indicates clearly the effect of dust density on restricting the movement of charge carriers, which in turn reduces inelastic plasma collisions.

Research on the Impact of Energy Price on Carbon Emission Intensity of China—An Empirical Study Based on LMDI Decomposition and Econometric Models

Taking the data of various sectors and three industries from 1980 to 2019 as the research object, the LMDI-I (Logarithmic Mean Divisia Index) multiplicative decomposition model, which is based on the principle of decomposing the change in energy consumption into the contribution of each factor, was used to decompose the carbon emission intensity into technological progress effect and economic structure changing effect. Meanwhile, quantitative econometric models of energy price, economic growth, energy consumption structure, and the two effects were also established. The empirical results showed that energy price, economic growth, and energy consumption structure significantly influenced the reduction in carbon emission intensity. A positive U-shaped relationship between energy prices and carbon emission intensity was overserved, and the rise of energy prices mainly drive the decline of carbon emission intensity through the effect of technological progress. However, the effect of economic structure driven by the rise of energy prices was limited; thus, further optimization of economic structure is needed. Additionally, the proportion of coal consumption was positively correlated with the technological progress effect and economic structure change effect, while the decrease in coal consumption proportion promoted the decline of carbon emission intensity. Finally, three recommendations based on the analysis were proposed.

Modeling the effects of heat stress in animal performance and enteric methane emissions in lactating dairy cows

Heat stress (HS) negatively affects dry matter intake (DMI), milk yield (MY), feed efficiency (FE), and free water intake (FWI) in dairy cows, with detrimental consequences to animal welfare, health, and profitability of dairy farms. Absolute enteric methane (CH4) emission, yield (CH4/DMI), and intensity (CH4/MY) may also be affected. Therefore, the goal of this study was to model the changes in dairy cow productivity, water intake, and absolute CH4 emissions, yield, and intensity with the progression (days of exposure) of a cyclical HS period in lactating dairy cows. Heat stress was induced by increasing the average temperature by 15°C (from 19°C in the thermoneutral period to 34°C) while keeping relative humidity constant at 20% (temperature-humidity index peaks of approximately 83) in climate-controlled chambers for up to 20 d. A database composed of individual records (n = 1,675) of DMI and MY from 82 heat-stressed lactating dairy cows housed in environmental chambers from 6 studies was used. Free water intake was also estimated based on DMI, dry matter, crude protein, sodium, and potassium content of the diets, and ambient temperature. Absolute CH4 emissions was estimated based on DMI, fatty acids, and dietary digestible neutral detergent fiber content of the diets. Generalized additive mixed-effects models were used to describe the relationships of DMI, MY, FE, and absolute CH4 emissions, yield, and intensity with HS. Dry matter intake and absolute CH4 emissions and yield reduced with the progression of HS up to 9 d, when it started to increase again up to 20 d. Milk yield and FE reduced with the progression of HS up to 20 d. Free water intake (kg/d) decreased during the exposure to HS mainly because of a reduction in DMI; however, when expressed in kg/kg of DMI it increased modestly. Methane intensity also reduced initially up to d 5 during HS exposure but then started to increase again following the DMI and MY pattern up to d 20. However, the reductions in CH4 emissions (absolute, yield, and intensity) occurred at the expense of decreases in DMI, MY, and FE, which are not desirable. This study provides quantitative predictions of the changes in animal performance (DMI, MY, FE, FWI) and CH4 emissions (absolute, yield, and intensity) with the progression of HS in lactating dairy cows. The models developed in this study could be used as a tool to help dairy nutritionists to decide when and how to adopt strategies to mitigate the negative effects of HS on animal health and performance and related environmental costs. Thus, more precise and accurate on-farm management decisions could be taken with the use of these models. However, application of the developed models outside of the ranges of temperature-humidity index and period of HS exposure included in this study is not recommended. Also, validation of predictive capacity of the models to predict CH4 emissions and FWI using data from in vivo studies where these variables are measured in heat-stressed lactating dairy cows is required before these models can be used.

Does manufacturing servitization reduce emissions intensity? evidence from China

ABSTRACT This paper investigates the impact on polluting emissions as a result of manufacturing industries in China offering services as well as products. We merge detailed firm-level statistics covering 2000 to 2011, and use two-way linear fixed effects regression to control for firm and year heterogeneities and a host of control variables. The empirical results show that manufacturing servitization significantly reduces the emission intensity of firms. This effect is achieved by improving the total factor productivity of firms, optimizing the efficiency of energy use, and increasing the share of the highly-skilled labour force. Moreover, the emission reduction effect of manufacturing servitization is more profound in the eastern and central regions, pollution-intensive industries, non-state-owned firms, and processing trade firms. In addition, our extended analysis shows that the emission reduction effects of manufacturing servitization can be strengthened through trade liberalization and cohort study. The major policy implication is that governments should undertake industrial policies that reinforce the positive effects of manufacturing servitization in order to achieve win-win outcomes in manufacturing upgrading and environmental protection.

Does Coal Consumption Control Policy Synergistically Control Emissions and Energy Intensity?

The coal consumption constraint policy (CCCP) serves a crucial role in the maintenance of environmental and economic sustainability for China. However, it is debatable whether the CCCP reduces emissions and energy intensity. The present study explores the impact and realization pathways of the CCCP on energy and emissions intensity at the city level from 2005 to 2019 using a time-varying difference-in-differences (DID) and structural equation model (SEM) approach. We find that the CCCP can control emissions and energy intensity synergistically. Particularly, the CCCP has significantly reduced SO2 and CO2 emission intensity and energy intensity by 0.1283%, 0.0747%, and 0.2493%, respectively. Moreover, the CCCP can effectively reduce emissions intensity through industrial restructuring, and technology advancement is the only effective way to reduce energy intensity. The study provides some valuable suggestions to enable the control of coal consumption.

Innovative nitrogen management strategy reduced N2O emission while maintaining high pepper yield in subtropical condition

High N fertilizer inputs in subtropical vegetable systems under the warm and humid climatic conditions increase the risk of nitrous oxide (N2O) emissions. However, there is limited information available on integrated N management strategies to reduce N2O emissions from intensive open-field vegetable systems in subtropical region. Two plot-based field experiments were conducted in subtropical southwest China to examine the effects of different N management strategies on N2O emissions from a typical open-field pepper (Capsicum annuum L.) production system. Experiment 1 included five N rates (0, 175, 250, 325, and 400 kg ha−1) with conventional urea. Experiment 2 included a 0 N control and four N sources (conventional urea, organic fertilizer, nitrification inhibitor-based enhanced efficiency fertilizer ENTEC26, and controlled release urea) applied under an optimized N rate (250 kg N ha−1). The results of Experiment 1 showed that cumulative N2O emission and emission factor were 4.05 kg N ha−1 season−1 and 0.96%, respectively, under the conventional management (N400). N2O emissions increased exponentially with increasing N rates. Compared to the N400 treatment, application of conventional urea at the optimal rate (250 kg N ha−1) significantly reduced cumulative N2O emissions by 54% while maintaining similar pepper yield. The results from Experiment 2 indicated that the use of enhanced efficiency fertilizers at the optimal rate further reduced N2O emission by 30%− 50% compared to conventional urea, while increasing pepper yield by 6.7%− 9.0%. This resulted in a 36%− 53% reduction of yield-scaled N2O emission intensity. In particular, the use of nitrification inhibitor was 28% more effective than controlled release urea for N2O mitigation. These results suggest that the application of enhanced efficiency fertilizers at an optimum N rate could produce more vegetables while reducing N2O emission, thereby promoting sustainable vegetable production in the subtropic regions.

Environmental credit constraints and pollution reduction: Evidence from China's blacklisting system for environmental fraud

Environmental performance-based credit mechanisms are among the tools policymakers can use to influence the polluting firms' behavior. In this study, we use China's blacklisting system for environmental fraud as a quasi-natural experiment to analyze the pollution-reducing effect of environmental credit constraints (ECCs). We operationalize our approach using a sample of 287 Chinese cities for the period 2008–2018 and find that ECCs help reduce emission intensity—a result that is both statistically significant and robust. Furthermore, our analysis suggests that ECCs can motivate producers to increase investment in technological innovation and optimize their factor allocation structure to improve green total factor productivity, thereby helping reduce their environmental impact. We demonstrate that the ECC-based schemes could be particularly effective in helping reduce pollution in regions with high enterprise credit dependence and relatively heavy presence of the manufacturing industry. In addition, these pollution-reducing effects are significant in regions with relatively strict environmental regulation. Hence, we argue that environmental credit systems could help policymakers provide polluting companies with additional incentives to voluntarily cut their emission levels and thus offer opportunities for diversifying the strategies policymakers can use to mitigate adverse environmental impacts.

Development of a Factorial Hypothetical Extraction Model for Analyzing Socioeconomic Environmental Effects of Carbon Emission Intensity Reduction

China has pledged to peak its carbon emissions before 2030 and achieve the net-zero ambition in the 2060s. Reducing the national carbon emission intensity can help achieve these ambitions effectively. To explore the tradeoff between emission reduction and system health, a factorial hypothetical extraction method has been proposed. It was applied to identify key carbon emission sectors, and further help formulate countermeasures on reducing the national emission intensity. A seven-factor factorial analysis was developed to evaluate the effects of factors (i.e., 7 countermeasures) and the combinations (i.e., 128 scenarios) on responsive variables (i.e., system health). Main effects and interactions for response variables were also detected between these factors. Results show that the most effective combination, i.e., simultaneously enlarging the production scales of agriculture and other services, and lessening those of metallurgy sectors, can help reduce emission intensity by −19.2%. Lessening the production scales of electricity-generation/metallurgy, and enlarging those of wholesale and retailing sectors, can help reduce national emission intensity, while these factors negatively impacted system sustainability and robustness. The mitigation effects of these countermeasures will be weakened if these countermeasures are implemented simultaneously. Enlarging the production scales of leasing and commercial services and other services sectors can help achieve a win-win outcome.

‘Going global’ and pollution in home country: Evidence from Chinese industrial firms

AbstractThe relationship between international investment and the environment is always concerned around the world, but the literature mainly focuses on the impact of foreign direct investment (FDI) (especially from developed countries to developing countries). Currently, many developing countries have regarded outward foreign direct investment (OFDI) as a critical task of economic development and encourage firms to ‘Going global’. After OFDI, how do firms' pollution emissions change? In this study, we employ the data of Chinese industrial firms to empirically answer this question. In particular, we combine inverse probability weighted matching with a difference‐in‐difference approach to identify the causal effect of OFDI on firm‐level pollution emissions. Our result indicates that OFDI leads to the reduction in both emission intensity and emission levels. This pollution reduction is driven by improving abatement technology and decreasing energy intensity. It potentially implies that OFDI reduces pollution emissions mainly through the ‘reverse technology spillover’ effect rather than ‘pollution transfer’ effect. In addition, pollution reductions caused by OFDI are prominent for local production OFDI and resource exploitation OFDI, OFDI to high‐income countries as well as capital‐intensive industries. Overall, this study not only provides an initial evidence for the relationship between OFDI and the environment at the firm level but also provides enlightenments for international investment and sustainable development.

Impact of International Trade on the Carbon Intensity of Human Well-Being

There has been a longstanding debate about the impact of international trade on the environment and human well-being, yet there is little known about such environment and human well-being trade-off. Here, we explore the effect of international trade on the carbon intensity of human well-being (CIWB) globally under the current global trade system and a hypothetical no-trade scenario. We found that between 1995 and 2015, CIWB of 41% of countries declined and 59% of countries increased, caused by international trade, and this resulted in a reduction of the global CIWB and a decline in CIWB inequality between countries. International trade decreased CIWB for high- and upper-middle-income countries and increased CIWB for lower- and middle-income countries. In addition, our results also show that decreases in emission intensity are the most important driver of lower CIWB and the percentage contribution of emission intensity to the improvement in CIWB increases with income. The reduction of emission intensity, population growth, and increase in life expectancy all contribute to CIWB reduction, while the consumption level is the primary factor driving CIWB growth. Our results underscore the importance of studying the impact of international trade on the CIWB of countries at different stages of development.

Differences in science-based target approaches and implications for carbon emission reductions at a sectoral level in Germany

As climate change becomes more apparent, companies increase their efforts to reduce greenhouse gas emission, both on a compulsory and voluntary level. The Science Based Targets initiative (SBTi) provides methods and guidelines for companies to align voluntary emission reduction targets with climate goals of the Paris Agreement. Two different approaches are provided: the absolute contraction approach (ACA), which aims for linear reduction in absolute emissions, and the physical intensity convergence approach (PICA), which targets equally reduced emission intensities within sectors. This paper examines how the interplay of ACA and PICA influences reduction targets and overall emission reduction levels. A cross-sectoral analysis is carried out to derive near- and long-term emission reduction targets for sectors specified in the German Climate Change Act. This is followed by a sector-specific analysis for the sectors residential and service buildings. To investigate the interplay of ACA and PICA within these sectors, a case study is carried out. By analysing several sectors, it was found that the combined SBTi budgets of the individual sectors lead to a range of 6.7 % by 2030, which could be as low as 333 MtCO2eq in the best case or as high as 355 MtCO2eq in the worst case. The sum of all sectoral science-based targets developed in the cross-sectoral analysis undercuts the overall emissions budgets for 2030 and 2040 specified in the German Climate Change Act by 16.3 %. The sectoral analysis complements these findings by showing that the interaction of ACA and PICA within a sector can lead to an increase in permitted future emissions, which would result in a slight exceedance of the 2040 emissions budget of 0.2 %. The co-existence of ACA and PICA can also lead to the 2040 emissions budget being undershot by around 24 % in the best case scenario. This paper shows that allowing companies to choose between ACA and PICA to develop emission reduction targets can lead to emissions exceedances. The SBTi should therefore consider approving only one approach for each sector.

Research on the Influence of Enterprise’s Digital Transformation on Carbon Emission Intensity——A Moderated Mediation Model

Digitalization and low-carbon development are parallel in the digital economy. In what ways does the development of low-carbon economy can be contributed by the digital transformation of enterprises? This paper analyzes the impact of digital transformation on carbon emissions from a micro perspective. Based on unbalanced panel data from 278 listed companies between 2010 and 2018, a double fixed-effect model is used to test the overall effects of digitalization on carbon emission intensity, the intermediary role of green technology innovation capacity and the regulatory effect of absorptive capacity. Results show that digital transformation of enterprises contributes to the reduction of carbon emission intensity, green technology innovation capability partially mediates the impact of digital transformation on carbon emission intensity, and absorptive capacity moderates the impact of digital transformation on green technology innovation capacity. Based above, this paper puts forward corresponding countermeasures from the aspects of digitalization, greening and low carbon.

Examining the interaction of technology adoption-diffusion and sectoral emission intensity in developing and emerging countries

This study offers a new perspective on the drivers of environmental sustainability for sector level (manufacturing, mining, agriculture, business, trade, and transport) analysis. In this case, country-level sectoral dynamic index for technology adoption and emission intensity were constructed to study the environmental efficiency effect of technology adoption and technology diffusion across tradable and non-tradable sectors by using empirical illustration for 49 developing and emerging countries during 1990–2018 period. By correcting for potential bias arising from endogeneity and cross-border spillover effects via cross-section dependence, results reveal long-term effects of technological changes. Importantly, it is shown that the environmental efficiency effect of technology adoption holds in technology-intensive sectors (i.e manufacturing, mining, agriculture) only at lower capitalization levels, thus establishing a U-shaped nexus of technology adoption and carbon emission. Additionally, it is found that trade networks reduce emission intensities by improving technology diffusion across all the tradable sectors and in transport sector. Moreover, trade alone mitigates carbon intensity across all the sectors while income per capita spur carbon intensity in the tradable sectors. From policy insight, the study identifies the need for stricter policy directives to scale up energy and clean technologies adoption in all sector activities.

How carbon emission prices accelerate net zero: Evidence from China's coal-fired power plants

China produced over half the world's coal-fired power capacity. Using a recent and comprehensive dataset of 1269 Chinese coal-fired power plants from 2009 to 2019, this paper provides empirical evidence of the impact of China's carbon trading pilot program on emissions regulation. Results show the significant potential for emissions intensity reduction due to increasing carbon prices, especially for low-risk, low-efficiency but high-cost plants, particularly those in China's midland and western regions. Rising marginal abatement costs and accelerated depreciation from carbon prices may encourage utilities to retire high-emission power plants sooner than originally planned, leading to lower emissions intensity. The average retirement years of China's power plants can be shortened by 1.8001 and 1.6862 years under R2CUT and R2LUMP scenarios, respectively, as Cao et al. (2016). This study offers new insights into the impact of carbon prices on power plants and has important policy implications.

Multi-dimensional Analysis of the Synergistic Effect of Pollution Reduction and Carbon Reduction in Tianjin Based on the STIRPAT Model

Based on the STIRPAT model, this study quantitatively analyzed the synergistic effect of pollution reduction and carbon reduction in Tianjin from three dimensions:total emission, emission reduction, and synergy coefficient. The results showed that the main emission sources of air pollutants and greenhouse gases in Tianjin were industrial sources, and the Pearson correlation coefficient of air pollutants and greenhouse gases was 0.984. The total population, urbanization rate, gross regional product, energy intensity, and carbon dioxide emission intensity were important factors affecting the synergistic effect of pollution reduction and carbon reduction in Tianjin. In 2011 and 2012, Tianjin's air pollutants and greenhouse gas emissions increased synergistically, and the synergistic effect coefficients were 0.18 and 0.17, respectively. From 2013 to 2014 and from 2018 to 2023, the air pollutant emission reduction and greenhouse gas emission increased, the synergistic effect coefficient was less than 0, and the pollution reduction and carbon reduction had no synergistic effect. In 2015-2017 and 2024-2060, air pollutants and greenhouse gas emissions were predicted to be reduced at the same time, with a synergistic effect coefficient ranging from 2.74 to 8.76. Tianjin had the conditions to enter the synergistic stage of pollution reduction and carbon reduction in 2024. The most important things for Tianjin to do to promote the synergy of pollution reduction and carbon reduction were to strictly control the total amount of greenhouse gas emissions, continue to promote the reduction in energy intensity and carbon dioxide emission intensity, and reasonably control the total population, urbanization rate, and regional GDP.

Can Innovation-Driven Policy Reduce China’s Carbon Emission Intensity?—A Quasi-Natural Experiment Based on the National Innovative City Pilot Policy

Innovation and carbon neutrality are hot topics nowadays and are important issues related to development quality, efficiency, and long-term sustainability. The purpose of this paper was to analyze the impact of innovation-driven policy on reducing carbon emission intensity. Using urban panel data from 2003 to 2018, this paper constructed a time-varying difference-in-difference model based on the natural experiment of national innovative city pilot policy and systematically examined the specific effects and mechanisms of innovation-driven policy on reducing carbon emission intensity. It was found that the innovation-driven policy represented by the national innovative city pilot policy can significantly reduce the carbon emission intensity in China, and this result was still valid after various robustness tests. The mechanism analysis showed that a reduction in carbon emission intensity was mainly achieved by innovation-driven promotion of green production technology progress and improvements in energy use efficiency. Further heterogeneity analysis showed that the policy had a more significant carbon reduction effect in cities with a strong innovation capability, large size, and low level of industrial structure. These research conclusions provide useful references for further understanding of the economic and social benefits of innovation-driven policy and effectively unleashing the carbon emission reduction effects of innovation-driven policy and promoting sustainable development.

Influence of Mixture Composition on Electrophysical Parameters and Emission Spectra of Tetrafluoromethane and Trifluoromethane Plasma with Nitrogen

The influence of the mixture composition on the electrophysical parameters and plasma emission spectra of mixtures of tetrafluoromethane and trifluoromethane with nitrogen under dc glow discharge conditions has been analyzed. It has been established that the reduced electric field strength changes nonlinearly with an increase in the proportion of the second gas in both mixtures. The reduced intensity of atomic fluorine emission in the CF4/N2 mixture is shown to pass through a maximum at a nitrogen volume fraction of 0.2, whereas a monotonic change in this dependence is observed for the CHF3/N2 mixture. The reduced emission intensities of CF2 radicals decrease monotonically with an increase in the nitrogen fraction in both mixtures.

Deterioration or improvement? Intermediate product import and enterprises' environmental performance

As an important link in Global Value Chain, intermediate product import is a key method to connect domestic market and foreign market. It can improve country's competitiveness and reduce country's total emissions through import substitution effect. However, the essence of this process is just the transfer of pollution from one country to another. Does importing intermediate products really reduce country's emission intensity and improve its emission efficiency? The above question is significant in reality, but it is still pending at present. In view of this, our research constructs the micro trade model and uses data of Chinese enterprises to investigate causal impact of intermediate product import on emission intensity. We can learn that importing intermediates significantly reduces enterprises' emission intensity. Further analyses shows that rise in enterprises' abatement investment and increase in productivity after importing lead to reduction in emission intensity. This study examines the positive role of intermediate product import in improving emission efficiency from perspective of product trade, revealing importance of intermediate product import in country's economic development and pollution reduction.

Can digital economy reduce carbon emission intensity? Empirical evidence from China's smart city pilot policies.

With the rapid development of digital technology worldwide, can the digital economy promote not only macroeconomic growth but also green and low-carbon economic development? On the basis of the urban panel data in China from 2000 to 2019, this study uses a staggered difference-in-difference (DID) model to explore whether or how the digital economy reduces carbon emission intensity. Results show the following. (1) The development of digital economy is conducive to reducing the carbon emission intensity of local cities, and the above conclusion is relatively stable. (2) There is strong heterogeneity in the impact of digital economy development on carbon emission intensity in different regions and different types of cities. Chinese smart city construction in southern cities, non-resource-based cities, and environment protection-focused cities significantly reduces urban carbon emission intensity. (3) Mechanism analysis shows that the digital economy can promote the upgrading of the industrial structure, improve the efficiency of energy utilization, improve the efficiency of environmental regulation, reduce the mobility of the urban population, improve the environmental protection awareness of residents, promote the modernization of social services, and achieve emission reduction from the "production side" and "living side." (4) Further analysis shows the change of the influence between the two in the space-time dimension. In the spatial dimension, the development of digital economy can promote the reduction of carbon emission intensity in neighboring cities. In the time dimension, the early stage of digital economy development may increase the intensity of urban carbon emissions. The energy-intensive nature of digital infrastructure leads to lower energy utilization efficiency in cities, thus improving urban carbon emission intensity.