CO2 Emission Intensity Research Articles

Life cycle assessment of solar PV water pumping system for carbon emissions reduction at a location: a case study

ABSTRACT The design of water supply systems powered by solar photovoltaic (PV) systems are installed for irrigation and other allied applications at remote rural areas which lack proper on-grid power systems. These systems have been operating successfully for several decades at locations receiving ample solar radiation, assisting in the reduction of carbon emissions. Hybrid life cycle assessment was performed in this study to determine the carbon emissions for a solar PV water pumping system (SPVWPS) in Xilin Gol League, Inner Mongolia. The carbon emission (g/mm3) produced by 1 m3 of water raised by 1 m was used as a reference in this assessment. The present analysis estimates the net CO2 emissions generated during the stages of production, transportation, construction, operation, maintenance, and recycling of SPVWPS. The results from SPVWPS were compared with CO2 emissions from diesel operated pumping systems. It was discovered that the carbon emission intensity produced during the 25-year operation period of SPVWPS was 0.80 g/mm3. The major CO2 emissions of SPVWPS were generated during the manufacturing stage totaled 2.02t, accounting for 55.19% of total emissions. When compared to the mobile diesel-powered water supply project, the CO2 emission intensity from SWPS was found to be about 0.55 times lower by about 1.46 g/mm3. As a result, the rapid development of SPVWPS in rural and pastoral areas represents the realization of rural low-carbon transformation and development, as well as the achievement of China’s “double carbon” reduction targets by 2050.

How does regional integration affect CO2 emission intensity? A natural experiment based on the expansion of the Yangtze River Delta, China

How does regional integration affect CO2 emission intensity? A natural experiment based on the expansion of the Yangtze River Delta, China

Role of household energy efficiency in shaping policy directives toward clean electricity transition in the United States: A nonparametric multivariate QQR approach

Despite the growing interest in energy transition policies, electricity generation in the U.S. remains heavily dependent on natural gas and coal. In this paper, we investigate the role of household energy efficiency in shaping policy directives toward a clean electricity transition in the U.S. through the use of a novel nonparametric multivariate quantile on quantile regression (M−QQR) over the period 1970 to 2040. The empirical results reveal that household energy-related efficiency has a positive effect on clean electricity transition across quantiles. This implies that household energy efficiency promotes clean electricity transition in the U.S. The results also show that energy expenditure and intensity of energy-related CO2 emissions are negatively related to clean electricity transition. However, the role of energy expenditures in the higher quantiles is positive. These findings align with the sensitivity and robustness analyses. This study offers significant contributions: First, the recently extended bivariate quantile-on-quantile regression to a multivariate case is applied. Second, we use historical and forecast datasets that span over seven decades. Overall, this study suggests the need for policymakers to utilize energy efficiency measures to stimulate transition towards clean electricity.

Increasing sustainability in palaeoproteomics by optimizing digestion times for large-scale archaeological bone analyses

Palaeoproteomic analysis of skeletal proteomes is used to provide taxonomic identifications for an increasing number of archaeological specimens. The success rate depends on a range of taphonomic factors and differences in the extraction protocols employed. By analyzing 12 archaeological bone specimens from two archaeological sites, we demonstrate that reducing digestion duration from 18 to 3hours has no measurable impact on the obtained taxonomic identifications. Peptide marker recovery, COL1 sequence coverage, or proteome complexity are also not significantly impacted. Although we observe minor differences in sequence coverage and glutamine deamidation, these are not consistent across our dataset. A 6-fold reduction in digestion time reduces electricity consumption, and therefore CO2 emission intensities. We furthermore demonstrate that working in 96-well plates further reduces electricity consumption by 60%, in comparison to individual microtubes. Reducing digestion time therefore has no impact on the taxonomic identifications, while reducing the environmental impact of palaeoproteomic projects.

Egalitarian governance and the green energy transition: an empirical test of 46 industrial economies, 1990–2020

AbstractHow well are the world´s major economies responding to the challenge of climate change? We address this question by assessing democratic governance styles, contrasted as more egalitarian from ones that are more liberal, on the green energy transition. We propose that egalitarian societies have a greater demand for balancing production, consumption, and rent-seeking demands with environmental ones, leading to more compromised solutions. We assess the effects of democratic style and measures of societal inequity on renewable energy production share, public environmentally related R&D expenditures, and CO2 emission intensity in 46 major industrialized economies in the period 1990 to 2020. Random and fixed effects regressions consistently show that while egalitarian and liberal democracies associate with greener policy measures, such as higher spending on environmental R&D budgets, egalitarian governance consistently associates with higher CO2 emissions. Contrary to the expectations of broad arguments highlighting the virtues of egalitarianism for mitigating climate change, the actual effects of greater egalitarian governance undermine the cause of climate gains. These results do not support the view that high consensus societies due to greater equity are transitioning to a greener economy faster than others even if they placate climate interests with higher investment in renewable energy. Future analyses need to focus more keenly on what measures enter green policies as mere “window dressing” while others make the hard choices for reducing overall emissions, which is ultimately how environmental gains should be measured.

Household carbon footprints of age groups in China and socioeconomic influencing factors

China has a large fastest-aging population, which would reshape household consumption patterns and influence global CO2 emissions. This study examines global CO2 emissions driven by household consumption (i.e., household carbon footprints, HCFs) of 34 age groups in China's 30 provinces and uncovers relevant socioeconomic influencing factors. Results show that China's population aging (i.e., the proportion of the elderly population) is conducive to global CO2 emission reduction during 2011–2014. This trend is mainly due to the relatively lower per capita HCFs of the elderly (1.7 t in 2014). In contrast, the per capita HCFs of the youth group are higher (3.3 t in 2014), mainly affected by the large expenditure on residence and transportation & communication. In addition, the HCFs of all age groups have increased during 2011–2014. Per capita expenditure is the most significant driver of this increase. The decline in CO2 emission intensity makes the largest contribution to reducing the HCFs of the youth group. For the aged group, expenditure structure change is the largest contributor to HCFs reduction. These findings reveal the differentiated impacts of China's household consumption by age on global CO2 emissions. This study lays the scientific foundation for deriving amelioration policies and achieving emission reduction targets in the process of population aging.

ANALYSIS OF COINTEGRATION AND CAUSALITY BETWEEN INDICATORS OF ECONOMIC GROWTH AND ENERGY EFFICIENCY OF EUROPEAN COUNTRIES

In modern conditions, when European countries have set themselves an extremely ambitious goal of reducing greenhouse gas emissions by at least 55% by 2030 compared to 1990 levels, it is important to analyze the cause-and-effect relationships between key indicators of energy efficiency of national economies and economic growth, the nature of their influence on each other. The article analyzes cointegration and causal relationships between panel data that determine the economic development and energy efficiency of 38 European countries for the period from 1995 to 2021. Stationary time series were analyzed for causality using the Dumitrescu Hurlin test, which, compared to the classical Granger test, more accurately takes into account the structure of panel data, namely cross-sectional relationships. The annual GDP growth rate has driven the intensity of CO2 emissions. For pairs of time series with the first level of integration, in the case of cointegration between them, a Vector Error Correction Model (VECM) was used to determine the type of long-term behaviour of the variables with their short-term feedback. Long-term causality was found from GDP per capita to the level of primary energy intensity of European countries. Exports of goods and services have proven to be a long-term cause of domestic consumption of natural gas and solid fossil fuels. Bidirectional long-term causality was found only between primary energy consumption and exports. It should be noted that in all short-term and long-term cause-and-effect relationships obtained in the article, economic development indicators are the cause for energy efficiency indicators. This signals that the level of energy efficiency of the European economy is determined to a large extent by the economic development of Europe in previous periods. ARDL models can be used to analyze causal relationships between time series that have different levels of integration.

Estimation of Energy Consumption and CO2 Emissions of the Water Supply Sector: A Seoul Metropolitan City (SMC) Case Study

A model that computes the per-unit process energy consumption, energy intensity, CO2 emission, and CO2 intensity of water treatment plants is developed. This model is used to estimate the total energy consumption of six water treatment plants in Seoul Metropolitan City (SMC), which is comprised 80–85% for finished water pumping, 6–10% for ozone disinfection, 2–4% for rapid mixing, and 1–3% for non-process loads. The model results are validated against actual data for 2020 and 2021. The net energy consumption considering renewable energy production and use is then calculated, and the corresponding level of CO2 emissions is predicted. Four scenarios based on the projected water requirements for the year 2045 were evaluated as follows: increased energy efficiency in finished water pumping (Scenario 1), increased renewable energy production in water treatment plants (Scenario 2), increased energy efficiency in raw water pumping (Scenario 3), and reduced water supply per capita (Scenario 4). Compared to a baseline do-nothing scenario (Scenario 0), the net energy consumption is reduced by 3.57%, 2.61%, 3.42%, and 4.67% for Scenarios 1–4, respectively. Scenario 4, which is a water-driven approach, is best for reducing CO2 emissions, while Scenario 1 and 3, which are energy-driven approaches, are more effective at reducing CO2 intensity.

Research on the Influencing Factors of CO2 Emission Intensity in Cement Industry

The cement industry, as a significant carbon-emitting sector, has a substantial impact on climate change. This study aims to explore the influencing factors of CO2 benchmark emission intensity in the cement industry to reveal how to reduce carbon emissions and enhance carbon emission management efficiency. We collected and analyzed data from numerous cement industry enterprises, including factors such as production processes, raw material selection, energy sources, and government policies. Through descriptive statistical analysis, correlation analysis, and regression analysis, we drew some key conclusions. The results indicate that production processes, raw material selection, and energy sources are the primary influencing factors for CO2 benchmark emission intensity. Enterprises employing wet production processes, selecting raw materials with higher silicon content, and utilizing renewable and efficient energy sources typically exhibit lower CO2 benchmark emission intensities. Government policies and regulations also have a significant impact on CO2 emissions, albeit with variations across countries and regions. These findings provide robust support for carbon emission management in the cement industry, aiding in the development of more sustainable production practices and emission reduction strategies.

How does decarbonization of the central heating industry affect employment? A spatiotemporal analysis from the perspective of urbanization

This study evaluates the spatiotemporal heterogeneous effects of decarbonizing the central heating industry on employment from the perspective of new-type urbanization based on an innovative theoretical framework. Our average estimated CO2 emission intensity of the central heating industry in China at the city-level decreased from 54.51 tCO2/100 m2 in 2012 to 47.24 tCO2/100 m2 in 2019. Decarbonization of the central heating industry may promote total employment in 72 % of the Chinese cities with the median effect is 0.005 % for each 1 % reduction of the heating carbon intensity. However, the promotion effect may be inhibited by ecological and environmental urbanization, while strengthening through population and land, economic, social, and urban–rural integration dimensions of urbanization. Our findings can provide policy implications for carbon emission control and new-type urbanization planning in cities to achieve stable employment.

Agroecological assessment of the efficiency of utilization of quail manure in the restoration of disturbed sod-podzolic soils with the formation of a stable herbage

The most acute environmental problems of our time include large volumes of bird droppings produced annually at large livestock complexes. At the same time, the sod-podzolic soils dominating in the Non-Chernozem zone of the European part of Russia are characterized by low reserves of humus, which quickly fall with intensive agricultural use and soil anthropogenic degradation. To restore degraded sod-podzolic soils, a peat-sand substrate enriched with compost from quail manure without and with the application of phosphogypsum to stabilize organic compounds of compost was used with the support of project No. 075-15-2021-1030 of the Ministry of Science and Higher Education of Russia. The vegetation experiment showed the maximum increase in plant biomass of the herbage in the variant with the combined use of compost and phosphogypsum: respectively, 30% higher than the control one. In the summer, there is an increased intensity of soil CO2 emissions in the variants with compost, but with a multiple more active increase in grass biomass growing, so one can talk about the atmosphere carbon sequestering nature of the technology of utilization of quail droppings during the restoration of disturbed sod-podzolic soils with the formation of a stable herbage.

Impacts of environmental feedbacks on the production of a Central Queensland beef enterprise in a future climate

CONTEXTUnderstanding climate change impacts on beef production enterprises in northern Australia is challenging due to the complexity of the system, which involves biophysical processes such as pasture and animal production, herd management, economics, emissions, and the interaction among these things. Modelling is a powerful tool to help the beef industry understand the impacts of climate change and to develop adaptation plans to help ensure enterprises remain economically viable over the long term. OBJECTIVEWe assess climate change impacts on a single specialised beef enterprise south-east of Moura (24.59°S, 150.09°E) in northern Australia's Central Queensland region. This is achieved by comparing enterprise performances during a 2030s climate and a 1975–2013 baseline period. METHODSWe used a calibrated pasture model called GRASP to simulate the farm's pasture growth under multiple scenarios for land conditions, grass basal areas and stocking rates for the baseline and 2030s climates and to construct pasture growth databases – known as datacubes. The datacubes provide a simplified representation of mean coupling between the herd dynamics and livestock production model (Crop Livestock Enterprise Model). The coupled whole-of-farm model was parameterised using enterprise data collected through interviews with the property owner and allowed for feedback between the pasture and livestock systems. The feedback capability allowed us to consider changes in land condition through stocking rates and their effect on pasture growth, animal weight gain, profit and CO2 emissions. RESULTS AND CONCLUSIONSWe found that warmer and drier climatic conditions during 2030s will reduce pasture growth in austral spring and summer but increase pasture growth in winter and autumn. Increased pasture growth in winter and autumn cannot compensate for the reduction in pasture growth in the warm seasons but can improve animal liveweight gain in winter and early spring. This leads to an overall increase in annual weight gain of steers (the cattle class that provides the main income source for this farm) while the CO2 emission intensity remains similar to the baseline period. Maintaining land condition under the 2030s climatic conditions considered will require a reduction in sustainable herd size, leading to lower beef production and lower profit under current pasture and herd management strategies. Impacts will likely differ from those described if a drier future is not realised. SIGNIFICANCEThis study provides a climate change impact assessment on a specialised beef enterprise (i) being distilled from individual ruminants, and (ii) considering environmental feedbacks in the interaction between pasture and livestock systems.

Study on energy use and carbon emission from manufacturing of OPC and blended cements in India.

The demand for production of cements is ever increasing to meet the infrastructure development globally. The energy and emission factors available for cements in most of the life cycle assessment (LCA) databases may not exactly suit for all the geographical locations. The main challenge in Indian scenario is the absence of database for LCA study. This study attempts to develop the energy and emission factors for the manufacturing of cements in Indian context. In the present study, five different cement manufacturing plants located in north, south, east, west and central zones of India are considered to assess the energy dissipation and carbon dioxide emission involved during the production of ordinary Portland cement (OPC). Most of the data is collected from the field, so that the energy and emission factors determined will be suitable for the zonal study. The study is then extended to assess the energy consumption and carbon dioxide emission for three blended cements, viz. Portland Pozzolan cement (PPC), Portland slag cement (PSC) and composite cement (CC) with permissible known replacement levels of fly ash, granulated blast furnace slag and both fly ash and slag, respectively. The average energy use and carbon emission is found to be on higher side in India by 15.14% and 12.64%, respectively, compared to other countries in manufacturing of cements. An average energy consumption in manufacturing of PPC, PSC and CC is found to be respectively 24.5%, 35.3% and 43.13% less compared to that of OPC. The CO2 emission intensity for OPC is found to vary between 893 and 940kg/tonne of cement from five different zones, and an average of respectively 24.8%, 40.97% and 47.18% lower CO2 emission was observed from PPC, PSC and CC compared to OPC. From the inventory results, CC has proven to be a more sustainable cement with low energy consumption and lower CO2 emission compared to other cements.

Heavy industrial aggregation area's green transformation optimisation pathways exploration with synergistic reduction pursue of CO2 and gaseous pollutants

A profound green transformation of China's heavy industrial aggregation regions is required to conquer severe air pollution, and fulfill carbon peak pledge. Here, to clarify the coordinated mechanism and an optimal roadmap for the reduction of CO2 and gaseous pollutants, we integrated input-output modelling, system dynamics, and multi-objective programming to construct a CO2 and gaseous pollutants synergistic reduction model initially; investigated incentive approaches from 2020 to 2035; Hebei, with the largest steel production in China, was adopted as a demonstrative region. Results revealed that intensive dual control of efficiency and structure in energy and industry can accelerate achieving carbon peak in 2029. In optimal case, CO2 emission intensity can reach a 75.2% reduction compared to 2020, and gaseous pollutants continue decline simultaneously (SO2 and NOx can drop by 63% and 48%); and the synergistic reduction level is expected to improve. Thus, vigorously develop decoupling between economy-air pollution-carbon reduction in Hebei. As opposed to efficiency improvement, structural adjustments were demonstrated to be more effective than short-term efficiency improvements. In addition, the estimated development potential of traditional heavy industries such as steel and petrochemicals is limited, whereas the equipment manufacturing industry, closely linked to traditional industries, is expected to continue its development. Furthermore, although in the electrification process, coal consumption is still needed because of its indispensable role in the production process of heavy industries. The results can facilitate policy-making for heavy industrial aggregation areas' green transformation in shaping policies and actions with clear objectives, effective measures, and sound coordination.

Emission intensities in the Australian National Electricity Market – An econometric analysis

This study examines the evolution of CO2 emission intensities in the wholesale electricity sector for the National Electricity Market (NEM) in Australia. Using daily data, we examine the impact of demand, changes in the generation mix, as well as the closure of major coal-fired power plants on emission intensities in the four largest regional markets of the NEM. Particular emphasis is also placed on the assessment of any potential association between the examined driving factors and major Australian climate and energy policies such as the 2012–2014 Carbon Pricing Mechanism (CPM) or the Renewable Energy Target (RET) scheme. Our results suggest that changes in renewable deployment can be considered as the principal factor affecting emission intensities of all regional markets. Moreover, the fossil fuel mixture effect, more precisely the reduction in coal-fired generation combined with the increase in generation from gas and renewables, also played a significant role in reducing emission intensities in the Australian power sector. Interestingly, our findings suggest that the influence of the implemented CPM was not too substantial and had only temporary effects on emission intensities.

Path mechanism and spatial spillover effect of green technology innovation on agricultural CO2 emission intensity: A case study in Jiangsu Province, China

Green technology innovation (GTI) is one of the most important factors influencing agricultural carbon emission intensity (ACEI). Various studies have explored the impact of GTI on ACEI, but the path mechanism has not been fully explained. This study incorporates GTI and ACEI into the constant elasticity of substitution (CES) production function and constructs a theoretical model to analyse their direct impact mechanisms. Drawing on the substitution effect theory and the Marshall–Arrow–Romer (MAR) externalities theory, this study introduces two regulatory mechanisms: optimization of energy structure and agricultural industry agglomeration (AIG). Additionally, it explores the pathway mechanisms under the influence of spatial spillover effects based on Tobler’s first law of geography. Then, taking Jiangsu Province in China as a case study, empirical tests are conducted using LSDVC and dynamic spatial SAR models. The results are as follows. (1) GTI effectively inhibits ACEI directly, and has significantly positive spatial spillover effects on ACEI reduction in the short and long terms. (2) Energy structure optimization positively regulates the effect of GTI on ACEI reduction, and energy structure optimization in nearby cities may help GTI restrain ACEI in the local city in the short term. (3) AIG has a positive regulating effect on GTI reducing ACEI, and the moderating effect of AIG has positive spillover effects in the short term. (4) When both regulatory pathways are employed simultaneously, the moderating effect of AIG in local or neighbouring areas is expected to become ineffective. These findings are useful for solving the problem of ACEI reduction by managing the transfer and distribution of GTI between different regions, considering spatial spillover and moderating effects.

Local carbon emission zone construction in the highly urbanized regions: Application of residential and transport CO2 emissions in Shanghai, China

Optimizing urban morphology can help city managers deploy internal carbon reduction strategies. However, due to the numerous factors that influence urban carbon emissions and the complex paths of their effects, existing research findings are diverse and difficult to compare. This study constructed the local carbon emission zone (LCEZ) which links the highly urbanization morphology profiles and CO2 emission intensity to favor summarizing the form characteristics for the low CO2 emission control in new communities. The approach involved selecting six indicators from the perspectives of urban external morphology, internal characteristics, and development intensity, and using geographically weighted regression (GWR) to identify three key factors. The selected factors were divided into low(1) medium(2) and high(3) categories and were combined with each other to construct the LCEZ. The nonparametric test and GeoDetector model were used to test the difference and similarity of LCEZs, respectively. The results showed that 1) The impacts of functional mixing entropy (FME), building height (BH) and road density (RD) on residential and transport CO2 emissions (RTCE) were relatively large and positive; 2) The low- and medium-FME areas were the major types of LCEZ; 3) The area proportions of the low FME LCEZs in different population areas of the RTCE cold spot regions were the highest (81.84%–88.25%); 4) It is recommended that the morphological feature values of compact-low rise-low network (1-1-1), mid compact-low rise-mid network (1-1-2), compact-mid rise-low network (1-2-1) and mid compact-mid rise-mid network (1-2-2) were taken as the low CO2 emission control of highly urbanized regions.

Transition towards dual control of CO2 emissions and intensity through supply chain management in China

To mitigate global climate change and achieve CO2 emissions reduction goals, China proposed to shift to dual control of total CO2 emissions (CE) and CO2 emissions intensity (CEI) as early as possible. Accurately assessing provincial sectoral CE and CEI and developing reasonable regulatory strategies is a prerequisite for achieving the goal of dual control. However, there is a lack of comprehensive analysis from different perspectives of the supply chain. Therefore, this paper evaluates the CE and CEI in provincial sectors of China in 2017 from production-based and consumption-based perspectives according to multi-regional input-output (MRIO) model. Then, we analyze the supply chain of transmission sector by betweenness-based method as a supplementary perspective. The results show that: (1) The CE and CEI from different perspectives are different and can complement each other. (2) Production and distribution of electric power and heat power in Inner Mongolia (P5D24), construction in Jiangsu (P10D27), distribution of electric power and heat power in Beijing (P1D24) are the critical sectors for dual control of CE and CEI from production, consumption, betweenness-based perspectives, respectively. (3) Construction in Jiangsu (P10D27) and Shanxi (P4D27) have the highest embodied CE and CEI in China respectively. Energy and raw material sectors from upstream supply chain contribute large CE to construction sectors. This research suggests that paying attention to critical sectors from different perspectives of the supply chain and taking different measures to decrease CO2 emissions. Taking both CE and CEI into consideration and allocating CO2 emissions reduction pressures reasonably among provincial sectors. At the same time, taking care of relevant upstream sectors of the supply chain to help a single sector achieve CO2 emissions reduction goals and promote China's transition to dual control of CE and CEI.

Industrial chain division and carbon emission intensity: The moderating effect of digitization

Industrial chain structure optimization and digital transformation are crucial factors for achieving carbon emission reduction goals. Based on China's non-competitive input-output tables, this paper constructed industrial chain panel data using the structural path analysis method. We explored the influence of industrial chain division (ICD) on CO2 emission intensity through panel fixed effects model, and examined the moderating effect of digitization. The research found that: (1) The ICD can significantly reduce CO2 emission intensity, the results are robust after some endogeneity tests. (2) The emission reduction effect brought by ICD will be more obvious in high-stage, high-energy consumption, and high-intelligence industrial chains. There is still room to improve the emission reduction brought by the division network effect. (3) Digitization plays a positive moderating role on this effect. Furthermore, digital manufacturing and digital services exhibit heterogeneity in various types of industrial chains. (4) The ICD can reduce carbon emission intensity through pathways such as intelligent transformation, technological innovation, and energy efficiency, and digitization has positively moderated these impact pathways. Based on research results, targeted policy suggestions are provided for optimizing industrial chain structure and promoting digital transformation.

Reducing the Energy Penalty of Retrofit Decarbonization in Combined Cycle Power Plants

Abstract This study is a continuation of previous work aimed at elucidating the effect of hydrogen-cofiring and exhaust gas recirculation (EGR) on combined cycle (CC) performance. The thermodynamic analysis was expanded to include postcombustion capture (PCC) by means of mono-ethanolamine (MEA). Attention was paid to net power output and thermal efficiency. Part-load operation of the CC without carbon capture was taken as a reference. Decarbonization solutions, in ascending order of complexity, included the following: (1) adding a PCC unit; (2) combining EGR with PCC, so as to exploit the increase in the flue gas CO2 concentration while reducing the exhaust gas flow delivered to the absorber; (3) including hydrogen cofiring at the largest capability dictated by the gas turbine (GT) combustion system, with the opportunity to explore a wider range of EGR rates, while still relying on PCC of the residual CO2 in flue gas, before discharge into the environment. Scenarios were first discussed under the same GT load for consistency with the published literature, thus enabling the validation of the modeling procedure. Then, CC net power production was assumed as the basis of comparison. The third solution was found to be the most promising thus minimizing both the energy penalty due to carbon capture and CO2 emission intensity (EI).