Unveiling the Spatial-Temporal Characteristics and Driving Factors of Greenhouse Gases and Atmospheric Pollutants Emissions of Energy Consumption in Shandong Province, China

Guangyang He, Wei Jiang (), Weidong Gao and Chang Lu
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Guangyang He: School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China
Wei Jiang: School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China
Weidong Gao: School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China
Chang Lu: School of Water Conservancy and Environment, University of Jinan, Jinan 250022, China

Sustainability, 2024, vol. 16, issue 3, 1-19

Abstract: As the largest energy-consuming province in China, Shandong faces the dual task of greenhouse gas (GHG) reduction and atmospheric pollution control. Based on the latest activity data and updated emission factors, this study establishes a high-resolution emission inventory (5 km × 5 km) for GHGs and main atmospheric pollutants from the energy consumption sectors of Shandong Province from 2010 to 2021, quantifies the relationship between social economic factors and GHGs and atmospheric pollutants emissions using the expanded stochastic environmental impact assessment (STIRPAT) model, and forecasts the future emission trend with the help of the scenario analysis method. Results indicate that the electricity and transportation sectors are the main contributors to all pollutants. Spatially, the high value of pollutants is mainly concentrated in the urban agglomerations of central and eastern Shandong. Up to 72% of GHGs and 50% of air pollution emissions are attributed to the top 10% of emission grids. Emission peaks occur mainly in summer and winter due to straw burning, increased utilization of temperature-controlled facilities, and expansion of plant capacity. Population, energy consumption, the proportion of secondary industry, and energy consumption intensity are the most significant influencing factors for pollutant emissions. Scenario analysis results indicate Shandong province can reach its carbon peak in 2027 without sacrificing population growth or economic progress.

Keywords: atmospheric pollutant; greenhouse gas; high-resolution emission inventory; spatial-temporal characteristics; extended STIRPAT model; scenario analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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