Utilizing Data Collaboration to Drive Nitrogen Pollution Mitigation and Carbon Emission Reduction at City Scale

Abstract

Human activities have largely altered global carbon and nitrogen biogeochemical cycle with urban development, increasing atmospheric greenhouse gases (GHGs) as well as reactive nitrogen (Nr) emissions. Urban data collaboration system has the potential to match resource demand and supply with big data on a fine time scale, which could benefit the reduction of GHGs and Nr emissions. Here, taking Hangzhou City Brain as a case study, we find that the system has promoted resource utilization efficiency in various aspects, including urban traffic, parking, healthcare, public affairs, industrial production, and agriculture, ranging from 4% to 158%. These improvements have reduced GHGs and Nr emissions by 1.5% and 6% at city scale in 2021, respectively, mainly in industrial and transportation sectors. These emission reductions could bring an annual total societal benefit of 77 million US dollar. Further implementation and optimization of city brain system could promote the achievement of carbon neutrality and pollution control synergistically.

Keywords: Data collaboration, Coordinated carbon / nitrogen emission mitigation, Resource utilization promotion, Sustainable city, Carbon emission peak