An integrated social-ecological indicator for low-carbon transition: evidence from the Beijing-Tianjin-Hebei, China

• Proposed a new productivity indicator that integrates social and natural ecosystems. • More than half of the BTH show a downward trend with spatial clustering patterns. • OPGD-MGWR methods reveal global trends and local differences in driving mechanism. • Night light intensity and population density dominates the carbon sink pattern. Excessive carbon emissions in the Beijing-Tianjin-Hebei region have severely hindered regional sustainable economic development. Investigating grid-scale carbon sources and sinks incorporating social systems is of great significance for advancing China’s dual-carbon goals. This study proposes a novel productivity indicator, Net Social-ecological system Productivity (NSP), which integrates human society and natural ecosystems, and clarifies its spatiotemporal distribution patterns and multivariate driving mechanisms. The results show that: (1) From 2002 to 2020, the NSP in the study area exhibited a significant negative growth rate of −26.188 g C·(m 2 ·a) −1 . The annual mean NSP displayed a spatial pattern of being lower in the east and higher in the west, as well as lower in the south and higher in the north, with low-value areas concentrated in urban zones of metropolitan regions. (2) The spatial distribution of NSP followed distinct clustering patterns. The Beijing-Tianjin area consistently formed a low-low cluster, while over half of the study area (50.4 %) showed a declining trend in NSP, particularly in counties such as Daxing, Dingzhou, Anping, and Feixiang. (3) Night light intensity, GDP density, and population density were the primary drivers of NSP (Q > 0.5). The interaction between night light intensity and population density had the strongest explanatory power (Q > 0.7). NSP was higher (indicating stronger carbon sequestration capacity) when night light intensity ranged from 0 to 250 lm/m 2 and population density ranged from 0 to 188 persons/km 2 . (4) The spatial correlations between NSP and explanatory variables varied significantly. NSP was positively correlated with average annual temperature and solar radiation but negatively correlated with secondary industry GDP and land surface temperature (LST). The findings provide valuable insights for policymakers in the Beijing-Tianjin-Hebei region to formulate targeted carbon reduction strategies and promote low-carbon economic development.