Driving Mechanism of Synergistic Efficiency in Reducing Pollution and Carbon: Evidence From 249 Green Parks DOI Open Access
Chuang Li, Keke Li, Liping Wang

и другие.

Geological Journal, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

ABSTRACT The green park serves as a significant spatial carrier for China's strategy to become manufacturing powerhouse and promote industrial transformation upgrading. It is crucial platform implementing driving the development of manufacturing, promoting harmonious coexistence between man nature in current era. main focus this study total 249 parks announced by Ministry Industry Information Technology, it employs multi‐time point PSM‐DID method investigate 280 prefecture‐level cities. results show that: (1) coefficient certification policy estimated have significantly negative impact at 1% significance level. (2) facilitates integration pollution reduction carbon efforts leveraging technology innovation government support. (3) effect has regional consistency resource heterogeneity. Therefore, great effects pathways on synergies reduction.

Язык: Английский

How does new urbanization affect urban carbon emissions? Evidence based on spatial spillover effects and mechanism tests DOI

Weimin Xiang,

Yeqiang Lan, Lei Gan

и другие.

Urban Climate, Год журнала: 2024, Номер 56, С. 102060 - 102060

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

7

Assessment of Urban Environmental Quality by Socioeconomic and Environmental Variables Using Open‐Source Datasets DOI

Tan Lingye,

Nayyer Saleem, Rana Waqar Aslam

и другие.

Transactions in GIS, Год журнала: 2024, Номер 28(7), С. 2526 - 2544

Опубликована: Сен. 22, 2024

ABSTRACT In this era of rapid development, environmental quality is an essential aspect sustainable development. A healthy urban environment supports, regulates, and provides livable conditions. areas, considerably affected by socioeconomic factors such as population expansion economic For decision‐making, it also significant for stakeholders policymakers to understand the impact on quality. While previous studies have examined quality, they often focused single cities or limited parameters. This research addresses these limitations conducting a comparative analysis two major Asian with similar demographic features, utilizing comprehensive set variables. Our innovative approach combines open‐source datasets advanced remote sensing techniques provide more holistic assessment over decades. We analyzed last decades selected parameters: surface greenness, moisture, land temperature. Lahore (Pakistan) Wuhan (China) were having approximately same features. Correlation matrix has been used assess relationship between variables social‐economic variables: carbon emission. coefficient indicated that correlates negatively greenness moisture both (−0.67 −0.71) District (−0.5 −0.75), respectively, while had positive relation temperature: 0.65 0.57 District, respectively. These effects are prominent within 10 km distance from city center, where substantial observed during time window.

Язык: Английский

Процитировано

7

The heat island effect, digital technology, and urban economic resilience: Evidence from China DOI

Xuanmei Cheng,

Fangting Ge,

Mark Xu

и другие.

Technological Forecasting and Social Change, Год журнала: 2024, Номер 209, С. 123802 - 123802

Опубликована: Окт. 14, 2024

Язык: Английский

Процитировано

7

Chinese FDI outflows and host country environment DOI
Massimiliano Caporin, Arusha Cooray, Bekhzod Kuziboev

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 366, С. 121675 - 121675

Опубликована: Июль 5, 2024

Язык: Английский

Процитировано

6

Improve carbon dioxide emission prediction in the Asia and Oceania (OECD): nature-inspired optimisation algorithms versus conventional machine learning DOI Creative Commons
Loke Kok Foong, Vojtěch Blažek, Lukáš Prokop

и другие.

Engineering Applications of Computational Fluid Mechanics, Год журнала: 2024, Номер 18(1)

Опубликована: Авг. 23, 2024

This paper investigates the application of three nature-inspired optimisation algorithms – SHO, MFO, and GOA combined with four machine learning methods Gaussian Processes, Linear Regression, MLP, Random Forest to enhance carbon dioxide emission prediction in OECD Asia Oceania region. The study uses historical emissions data, socioeconomic indicators such as GDP, population density, energy consumption, urbanisation rates, environmental temperature, precipitation, forest cover. Through comprehensive experimentation, evaluates performance each combination, revealing varying effectiveness levels. MFO-MLP combination achieved highest accuracy R2 values 0.9996 0.9995 RMSE 11.7065 12.8890 for training testing datasets, respectively. GOA-MLP configuration 0.9994 0.99934 15.01306 14.59333. SHO-MLP while effective, showed lower 0.9915 0.9946 55.4516 41.575. findings suggest hybrid techniques can significantly compared conventional methods. research provides valuable insights policymakers stakeholders, indicating that optimised models support more informed effective policy-making sustainability efforts Future should explore additional ensemble improve robustness accuracy. These offer a robust tool forecast accurately, aiding developing targeted strategies reduce footprints achieve climate goals.

Язык: Английский

Процитировано

5

Digital technology-enabled carbon-neutral management: A mechanism of supply chain digitalization in carbon performance DOI
Lixu Li, Wenwen Zhu,

Long Wei

и другие.

Technological Forecasting and Social Change, Год журнала: 2024, Номер 210, С. 123834 - 123834

Опубликована: Окт. 31, 2024

Язык: Английский

Процитировано

5

Data analytics driving net zero tracker for renewable energy DOI Creative Commons
Bankole I. Oladapo, Mattew A. Olawumi, Temitope Olumide Olugbade

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2024, Номер 208, С. 115061 - 115061

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

5

Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China DOI
Xiao Zhang, Shuhui Sun, Shunbo Yao

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 358, С. 120788 - 120788

Опубликована: Апрель 11, 2024

Язык: Английский

Процитировано

4

Renewable Energy Credits Transforming Market Dynamics DOI Open Access
Bankole I. Oladapo,

Mattew A. Olawumi,

Francis T. Omigbodun

и другие.

Sustainability, Год журнала: 2024, Номер 16(19), С. 8602 - 8602

Опубликована: Окт. 3, 2024

This research uses advanced statistical methods to examine climate change mitigation policies’ economic and environmental impacts. The primary objective is assess the effectiveness of carbon pricing, renewable energy subsidies, emission trading schemes, regulatory standards in reducing CO2 emissions, fostering growth, promoting employment. A mixed-methods approach was employed, combining regression analysis, cost–benefit analysis (CBA), computable general equilibrium (CGE) models. Data were collected from national global databases, sensitivity analyses conducted ensure robustness findings. Key findings revealed a statistically significant reduction emissions by 0.45% for each unit increase pricing (p < 0.01). Renewable subsidies positively correlated with 3.5% employment green sector 0.05). Emission schemes projected GDP 1.2% over decade However, chi-square tests indicated that disproportionately affects low-income households 0.05), highlighting need compensatory policies. study concluded balanced policy mix, tailored contexts, can optimise outcomes while addressing social equity concerns. Error margins projections remained below ±0.3%, confirming models’ reliability.

Язык: Английский

Процитировано

4

Does green transportation affect carbon emission efficiency? Evidence from a quasi-experimental study in China DOI
Ruizeng Zhao, Yan Jiang, Xinyue Wang

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122815 - 122815

Опубликована: Окт. 4, 2024

Язык: Английский

Процитировано

4