The Paris agreement is a unified arrangement for the global response to climate change and entered into force on 4 November 2016. Its long-term goal is to hold the global average temperature rise well below 2 °C. China is committed to achieving carbon neutrality by 2060 through various measures, one of which is green technology innovation (GTI). This paper aims to analyze the levels of GTI in 30 provinces in mainland China between 2001 and 2019. It uses the spatial econometric models and panel threshold models along with the slack based measure (SBM) and Global Malmquist-Luenberger (GML) index to analyze the spatial spillover and nonlinear effects of GTI on regional carbon emissions. The results show that GTI achieves growth every year, but the innovation efficiency was low. China’s total carbon dioxide emissions were increasing at a marginal rate, but the carbon emission intensity was declining year by year. Carbon emissions were spatially correlated and show significant positive agglomeration characteristics. The spatial spillover of GTI plays an important role in reducing carbon dioxide emissions. In the underdeveloped regions in China, this emission reduction effect was even more significant.

Eco-compensation for watershed services (EWS), or the more general payments for ecosystem services, is an incentive-based environmental policy instrument. With official documents and first-hand data from fieldwork, we analyze China’s 17 EWS pilot schemes across 16 provinces. Major environmental crises in China can partly be caused by the inadequate incentives for local governments to forcefully implement the environmental laws and policies. EWS schemes in China mainly target local governments in upstream and downstream watersheds, rather than the private entities in normal applications elsewhere, to provide economic incentives and to encourage their enforcement activities.

Megacities are increasingly confronted with diverse sources of noise pollution, which pose significant challenges to effective noise abatement. This paper employs the ‘Framework for Human Health Risk Assessment to Inform Decision Making’ and integrates residents’ self-assessed health impacts to replace traditional instrument-based noise measurements. The goal is to explore how soundscape co-governance can be encouraged as a strategy to manage noise in megacities. Using the Extended Theory of Planned Behavior, we analyze the contradiction between risk identification and risk solution, considering factors such as noise source, exposure, and sensitivity. Our findings indicate that non-industrial noise in megacities causes more severe health impacts, as assessed by residents, compared to industrial noise. However, public participation in soundscape co-governance is notably lower for non-industrial noise. Furthermore, residents living closest to noise sources, within 0–100 m, experience the most significant health impacts yet are the least active in participating in soundscape co-governance. Similarly, residents with higher education levels also experience greater health impacts from noise but are less active in participating in soundscape co-governance compared to others. The primary reason for this inconsistency between the health impacts on residents and their participation in soundscape co-governance is the reliance on the traditional environmental governance system. To enhance health-oriented soundscape co-governance in megacities, it is recommended to adopt community-based co-governance, implement refined governance strategies based on exposure levels, promote public integration and strengthen connections between the government and the public.