With more and more reports of climatic fluctuations and catastrophes, global warming has gained more worldwide attention in recent years (IPCC, 2007(IPCC, , 2014. Currently, the representative climate indicators, for example, snow, glaciers, permafrost, and alpine tundra particularly in high altitudes and latitudes, have proven more sensitive and vulnerable to climate change than other land surface components (

Environmental auditing (EA) is an efficient tool for supervising environmental governance for the realization of economic and social sustainable development. However, the extent to which EA influences the implementation of environmental protection projects and the dominating socioeconomic factors affecting the implementation of EA are unclear. Due to limited data availability, reports investigating this issue are relatively scarce. Based on annual investigation data from the International Organisation of Supreme Audit Institutions regarding the implementation of world EA projects between 2003 and 2013, this paper performed exploratory spatial data analysis to analyze the spatial correlations of EA projects in 204 countries/regions worldwide. In addition, spatial regression models for the year 2013 were established. The findings suggest that (I) high-high regions were mainly concentrated in North America, Europe, and parts of Latin America. The local implementation of EA had strong spatial interactive effects and was heavily influenced by adjacent regions. An experimental area that has already implemented EA can influence its adjacent regions, and the surrounding regions may learn from such implementation. (II) The spatial regression coefficient of the spatial lag model was 0.323 and highly significant (p < 0.001) compared to the traditional regression model. After considering the spatial variables, the importance of CO 2 emissions decreased by 1.7%, while environmental input and per capita income decreased by 0.7% and 1%, respectively. The influence of these factors on the implementation of EA was driven by the factor of spatial proximity, which was a critical factor influencing the results. (III) In general, socioeconomic development level, environmental protection investment, and other factors, such as CO 2 emission level and degree of social informatization, all increased the efficiency of EA implementation. These conclusions emphasize the important role of EA in helping local governments with environmental management and sustainable development.