Exploring the complex trade-offs and synergies of global ecosystem services.

The trade-off and synergy relationship of ecosystem services is an important topic in the current assessment. The value of each service provided by the ecosystem is substantially affected by human activities, and conversely, its changes will also affect the relevant human decisions. Due to varying trade-offs among ecosystem services and synergies between them that can either increase or decrease, it is difficult to optimize multiple ecosystem services simultaneously, making it a huge challenge for ecosystem management. This study firstly develops a global Gross Ecosystem Product (GEP) accounting framework. It uses remote sensing data with a spatial resolution of 1 km to estimate the ecosystem services of forests, wetlands, grasslands, deserts, and farmlands in 179 major countries in 2018. The results show that the range of global GEP values is USD 112-197 trillion, with an average value of USD 155 trillion (the constant price), and the ratio of GEP to gross domestic product (GDP) is 1.85. The trade-offs and the synergies among different ecosystem services in each continent and income group have been further explored. We found a correspondence between the income levels and the synergy among ecosystem services within each nation. Among specific ecosystem services, there are strong synergies between oxygen release, climate regulation, and carbon sequestration services. A trade-off relationship has been observed between flood regulation and other services, such as water conservation and soil retention services in low-income countries. The results will help clarify the roles and the feedback mechanisms between different stakeholders and provide a scientific basis for optimizing ecosystem management and implementing ecological compensation schemes to enhance human well-being.

Comparative analysis of visual amenity services valuation: A nationwide assessment through propensity scoring matching and hedonic regression.

Conventional hedonic valuations of environmental amenities and cultural ecosystem services (CES) expose two limitations. First, related studies are unable to fully capture the value of visual amenity services which synergistically contribute and enhance the provision of valuable CES together with recreation, educational and spiritual services. Second, studies using linear hedonic regression cannot address potential bias resulting from multicollinearity in independent variables. We found that popular choices of covariates are correlated with the main amenity variable, which can lead to an undermined estimation precision. Therefore, to address those shortcomings, we first employed a specific proxy dummy variable to assign treatment and control individuals based on the service type. Second, we adopted propensity score matching (PSM) methodology to match treatment and control observations conditional on overlapping baseline covariates in order to avoid collinearity. Then, we carried out a comparative evaluation of a nationwide visual amenity service of the ocean ecosystem in China, via our new PSM-based average treatment effects (ATE) methodology and a conventional linear hedonic regression. Two methodologies showed opposite results, with an 8.3% premium in apartment price via PSM-ATE and a negative 0.9% premium via hedonic linear regression. Via a novel evaluation method and a nationwide case study, we conclude that diversifying and enriching the current methodology should be the priority for environmental amenity and cultural ecosystem services-related valuations.

Interaction Patterns between Climate Action and Air Cleaning in China: A Two-Way Evaluation Based on an Ensemble Learning Approach.

China will attempt to achieve its simultaneous goals in 2060, whereby carbon neutrality will be accomplished and the PM2.5 (fine particulate matter) level is expected to remain below 10 µg/m3. Identifying interaction patterns between air cleaning and climate action represents an important step to obtain cobenefits. Here, we used a random sampling strategy through the combination of chemical transport modeling and machine learning approach to capture the interaction effects from two perspectives in which the driving forces of both climate action and air cleaning measures were compared. We revealed that climate action where carbon emissions were decreased to 1.9 Bt (billion tons) could lead to a PM2.5 level of 12.4 µg/m3 (95% CI (confidence interval): 10.2-14.6 µg/m3) in 2060, while air cleaning could force carbon emissions to reach 1.93 Bt (95% CI: 0.79-3.19 Bt) to achieve net carbon neutrality based on the potential carbon sinks in 2060. Additional controls targeting primary PM2.5, ammonia, and volatile organic compounds were required as supplements to overcome the partial lack of climate action. Our study provides novel insights into the cobenefits of air-quality improvement and climate change mitigation, indicating that the effect of air cleaning on the simultaneous goals might have been underestimated before.