With increasing urbanization in China, the traffic-induced urban environmental noise pollution problem is becoming more and more serious, and it has become a common urban malady that cannot be ignored. Traffic green belts are an important part of the urban ecosystem and play a role in traffic noise reduction, and simultaneously provide ecosystem services, such as creating a natural landscape and retaining dust. Therefore, they are a category of Nature-based Solutions (NbSs) that have multiple ecosystem service provisions. The relationship between NbSs and urban ecosystem services is one of the current research hot spots. However, regarding the assessment of ecosystem services on the urban scale, the role of vegetation in reducing noise pollution as a service has rarely been studied. Taking Shenzhen City as an example, through monitoring 217 sample plots in the city, this paper analyzes the relationship between vegetation coverage and the ability of green belts to reduce noise by using the IUEMS platform combined with the high-resolution spatial distribution data of green spaces. Then, we evaluated the product amount and the value of the roadside green belts in Shenzhen when acting as a noise reduction service. The work of this study, to a certain extent, improves the problems related to the inadequate consideration of vegetation characteristics in current urban-scale noise assessment models. The results show the following: (i) In the respective analysis buffer zones of the Grade I to Grade IV roads in Shenzhen, on average, for every 1% increase in the vegetation coverage of green belts, noise can be reduced by 0.4 dB, 1.0 dB, 0.2 dB, and 0.6 dB, respectively. (ii) The product value of the noise reduction service provided by roadside green belts is CNY 1.16 billion in Shenzhen. (iii) The road traffic noise greatly exceeds the standard in Shenzhen, but traffic noise can be decreased by increasing the vegetation coverage of green belts. This is not only beneficial to the scientific understanding of the ecological service value of green spaces by evaluating the noise reduction service of traffic green belts, as well as its influencing factors, but is also beneficial to making improvements in construction and management ideas for urban green spaces.

Clarifying the pattern of the urban greenhouse gas (GHG) budget and its influencing factors is the basis of promoting urban low-carbon development. This paper takes Beijing and Shenzhen—the capital city and the most rapidly developing city in China, respectively—as case studies, comprehensively accounts their GHG budgets from 2005 to 2020, and investigates and compares the factors affecting their GHG budgets. The total GHG emissions in Beijing were lowest in 2005 (160.3 TgCO2 equivalents) and peaked at 227.7 TgCO2 equivalents in 2019, and then decreased to 209.1 TgCO2 equivalents in 2020. Meanwhile, the total GHG emissions in Shenzhen gradually increased from 36.0 TgCO2 equivalents in 2005 to 121.4 TgCO2 equivalents in 2019, and then decreased to 119.1 TgCO2 equivalents in 2020. The energy activity sector was the greatest contributor to GHG emissions in this period, accounting for 82.5% and 76.0% of the total GHG emissions in Beijing and Shenzhen, respectively. The carbon sink of the ecosystems of these two cities could absorb only small parts of their emissions, and the neutralization rates of sinks ranged from 1.7% to 2.3% in Beijing and from 0.3% to 1.5% in Shenzhen. The enhancement of population, economic product, and consumption increased the greenhouse gas emissions in both cities. A 1% increase in population size, per capita GD (gross domestic product), and residential consumption level would increase total GHG emissions by 0.181%, 0.019%, and 0.030% in Beijing, respectively. The corresponding increases in Shenzhen would be 0.180%, 0.243%, and 0.172%, respectively. The household size had opposite effects on the two cities, i.e., a 1% increase in household size would increase GHG emissions by 0.487% in Shenzhen but reduce them by 2.083% in Beijing. Each 1% increase in secondary industry and energy intensity would reduce GHG emissions by 0.553% and 0.110% in Shenzhen, respectively, which are more significant reductions than those in Beijing.

Against a background of high-speed development and the expansion of built land surface, there has been widespread encroachment of natural habitats (henceforth “eco-spaces”). It becomes correspondingly difficult to improve the value of urban ecosystem services, since current assessments of land still primarily focus on use value (e.g., when nature and its products are converted and consumed), while the regulation and non-material services provided by eco-spaces are often ignored. In order to assess the rate of return on land transfers of eco-space, theories such as strong sustainable development, ecological land rental, natural resource ownership and opportunity costs were synthesized to construct an eco-space transfer cost–benefit analysis model, which is based on the value of ecosystem services. This study used the Futian Mangrove Ecological Park in the megacity of Shenzhen as a case study. To estimate the social value, which more comprehensively captures ecosystem services and economic value from eco-space, we used a counterfactual scenario of residential land development (the most plausible alternative land use scenario). This allowed us to calculate the rate of return from eco-space use change. The result of the total and annual rates of return over a projected 70-year timeframe were −10.76% and −0.16%, respectively. Accordingly, we suggest that management of the mangrove park should change the pricing strategy to better align the social benefits that it generates with the payments sustaining it. This case study provides instructive lessons for the management of eco-space in large urban settings.