Research on the Prediction and Implementation Path of Carbon Peaking in Daqing City DOI
Yu Qi,

Guohua Fan

Journal of statistics and economics., Journal Year: 2024, Volume and Issue: 1(6), P. 24 - 33

Published: Dec. 1, 2024

This study selects carbon emission data from Daqing City 2001 to 2023 as the subject of analysis, employs STIRPAT model and ridge regression method decompose key factors affecting emissions, combines scenario analysis construct 32 different combined scenarios predict emissions peak time 2024 2035. results show that are generally positively correlated with City; Under baseline scenario, is expected reach its in 2030, while under single pathway scenarios, likely achieve early 2025. Based on prediction results, propose suggestions both industry technology aspects, take lead achieving peak.

Language: Английский

How to Forecast Daily Carbon Emissions During Public Health Emergencies: A Novel Self-Attention Multi-Neuron Time Series Model DOI

Yilong Wang,

Haoran Wang, Junjie Chen

et al.

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102502 - 102502

Published: March 1, 2025

Language: Английский

Citations

0

Forecasting carbon dioxide emissions using adjacent accumulation multivariable grey model DOI
Wei Yang,

Zhengran Qiao,

Lifeng Wu

et al.

Gondwana Research, Journal Year: 2024, Volume and Issue: 134, P. 107 - 122

Published: July 9, 2024

Language: Английский

Citations

3

How will ecosystem carbon sequestration contribute to the reduction of regional carbon emissions in the future? analysis based on the MOP-PLUS model framework DOI Creative Commons
Yalei Yang, Hong Wang, Xiaobing Li

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 156, P. 111156 - 111156

Published: Oct. 27, 2023

Carbon neutralization of land use and cover (LULC) has become an important way for countries to cope with future climate change. Existing studies focus on the quantification analysis historical current carbon storage emissions but lack understanding LULC emissions, which limits practical guiding value research findings regional dynamic management scientific decision-making. In this study, temporal spatial distribution patterns dynamics in different ecosystems, such as forest, cropland grassland, West Liao River Basin (WLRB) since 1990 were quantitatively assessed. Grey multiple objective programming (G-MOP) patch‑generating simulation (PLUS) models used predict distribution, under sustainable development scenario (SDS) WLRB 2030 2060, a comparative was performed other scenarios. The overall area grassland forest ecosystems showed upwards trend from 2020, while farmland slightly decreased. western part WLRB, net ecosystem production (NEP) high aggregation, low NEP aggregation effect urban area. Under economic (EDS) impervious layers will be further expanded, highest, amount lowest. ecological protection (EPS), water increased significantly, lowest, highest. SDS scenario, areas cropland, layer body are moderate, budget is better than that natural (NDS). these three scenarios, barren lower scenario. Considering benefit, benefit budget, best performance. This study provides new perspective discussing status small-scale watershed combines goals "sustainable development" "dual carbon". It data-supported basis diversified compensation mechanism neutrality well insights formulation optimization policies.

Language: Английский

Citations

8

Assessing the efficiency and the justice of energy transformation for the United States of America, China, and the European Union DOI
Pingkuo Liu, Ruiqi Zhao, Xue Han

et al.

Sustainable Development, Journal Year: 2023, Volume and Issue: 31(5), P. 3387 - 3407

Published: May 3, 2023

Abstract A conceptual framework is constructed to discuss the Energy Transformation Efficiency and Justice for Carbon Neutrality sustainable development. Both Slack Based Measure‐based Model improved are applied measure transformation efficiency justice respectively. Then empirical analysis, influencing mechanism of energy on economy analyzed by using panel data USA, China EU from 2000 2020 with Panel Smooth Transition Regression (PSTR). The results reveal that: requires a subtle balance between three essential inputs two important outputs, while associated five dimensions can describe both equal opportunity procedural justice. improving year year, they not completely mutually exclusive at present. As far as performance concerned, best all justice, USA better than but efficiency. In terms interrelationship, there an obvious Regime Switching Effect when growth. Furthermore, note that state transition be limited economic situation sector in each economy.

Language: Английский

Citations

7

Deep neural network for investment decision planning on low-carbon transition in power grid DOI Creative Commons
M Wang, Yixiao Wang,

Bobo Chen

et al.

International Journal of Low-Carbon Technologies, Journal Year: 2024, Volume and Issue: 19, P. 1368 - 1379

Published: Jan. 1, 2024

Abstract With the urgency of mitigating global warming, low-carbon transformation power grid systems has emerged as a pivotal industry upgrade for sustainable development. We proposed novel deep neural network-based approach investment decision planning in grids, which aimed to address multidimensional key indicators related and provided reliable electricity layouts plans system decisions. To achieve this, three targeted branch models were established, encompassing behavior, production consumption, predictions new capacity investment. These effectively tackled challenges associated with distribution, price scheduling, carbon quotas, feasibility generation technologies. Subsequently, model was constructed, employing spatiotemporal networks recurrent networks, integrated aforementioned incorporated existing data. A comparative analysis conducted, examining predicted results against actual values from perspectives: portfolio, economy, overall plans. The demonstrated effectiveness our method accurately predicting future installed diverse technologies, sustainability indices, returns. Notably, achieves an impressive forecasting accuracy over 90% compared past 4 years.

Language: Английский

Citations

2

The multiple empowerment effects of digital transformation on carbon emissions in manufacturing industry from the prospective of factor allocation: Theoretical analysis and empirical evidence DOI

Yingmei Zhao,

Wenping Wang

Environmental Impact Assessment Review, Journal Year: 2024, Volume and Issue: 110, P. 107698 - 107698

Published: Oct. 22, 2024

Language: Английский

Citations

2

Critical review of nuclear power plant carbon emissions DOI Creative Commons

Bojie Liu,

Binbin Peng, Fei Lu

et al.

Frontiers in Energy Research, Journal Year: 2023, Volume and Issue: 11

Published: Sept. 19, 2023

Nuclear power plays a crucial role in achieving the target of carbon neutrality to build sustainable society. However, it is not “carbon-free” when considering its entire life cycle. Therefore, accurate accounting and monitoring generated emissions are required avoid miscalculations nuclear energy as clean source. In this study, life-cycle plants (NPPs) with different reactor types reviewed. addition characteristic differences among reactors, disparities review results originate from varying at respective stages fuel cycle, technology choices each stage methods boundaries. The resulting NPP construction operation underestimated due limited data methods, which creates uncertainty evaluation emissions. An integrated framework for NPPs (CACO-NPP) proposed. This aims improve accuracy originating NPPs. emerging Generation III latest technology, HPR1000 (an advanced pressurized water reactor), was adopted case study. show that total vegetation loss, equipment manufacturing labor input during 1232.91 Gg CO 2 intensity 1.31 g /kWh, indicating notable mitigation capability By combining maturity successive design improvements, such could be further reduced. development very important realizing China’s target.

Language: Английский

Citations

5

Research on Carbon Emission Characteristics and Mitigation Pathways in the Vehicle Fuel Cycle: A Case Study of Guangdong Province DOI Creative Commons
Jianjun Liu,

Yinping Luo,

Qianru Zhu

et al.

Atmosphere, Journal Year: 2023, Volume and Issue: 15(1), P. 3 - 3

Published: Dec. 20, 2023

This study presents a comprehensive analysis of vehicle ownership, energy consumption, and carbon emissions in Guangdong Province, China, from 2020 to 2035 under different scenarios. Key findings highlight the province’s pursuit peak goals provide valuable insights into strategies achieve them. Vehicle ownership is projected exceed 48 million by 2035, which represents doubling 2020. Under both scenarios, internal combustion engine will around 2030 then gradually decline, while enhanced scenario, electric 40% 2035. Enhanced efficiency reduced annual mileage lead 17% reduction gasoline diesel consumption At same time, there be substantial five- six-fold increase electricity for vehicles compared Both scenarios before 2030, with scenario achieving this year earlier. The outperforms baseline, reducing about 21.2% 8% relative Pure exhibit significant advantage per their counterparts. Encouraging new vehicles, especially pure ones, accelerates lowers overall emissions. Accelerating adoption per-vehicle fuel average mileage, optimizing transportation modes are crucial peaking cycle. Policy recommendations focus on promoting transportation, advancing research technology.

Language: Английский

Citations

2

Predicting the Change of CO2 Emissions Using a BNN-FA Method: A Case Study of Hebei Province DOI
Zhan Wang, Yongping Li, Guohe Huang

et al.

Environmental science and engineering, Journal Year: 2024, Volume and Issue: unknown, P. 65 - 74

Published: Jan. 1, 2024

Language: Английский

Citations

0

A Waste Extended Input-Output-based Transformer-LSTM method for analyzing hazardous waste reduction patterns: A case study of Shanghai DOI
Qian Zhou, Jicui Cui, Lan Wang

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 458, P. 142435 - 142435

Published: May 8, 2024

Language: Английский

Citations

0