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Various types of protected areas (PAs) are important for biodiversity conservation and essential for the 2050 Vision for Biodiversity. Rapid urban expansion affects the effectiveness of PAs in many ways. However, we still lack a clear understanding of the spatial relationship between urban expansion and different types of PAs in China during the last 30 years. Here, we analyzed the spatiotemporal changes in such relationship based on the boundaries of 2622 terrestrial PAs, as well as local Moran's and the Kruskal-Wallis H test during the period of 1992–2020 at the national, regional and provincial scales. The results showed that the number of PA threaten by urban expansion at the national scale fluctuated over time (10 to 80), while the median of the nearest distances between PAs and urban built-up areas decreased from 80.4 km to 2.6 km. At the regional scale, the PAs in east China were more affected by urban expansion than the ones in west China, with higher number of threatened PAs and closer distance between PAs and urban built-up areas. More importantly, non-national PAs were more severely affected by urban expansion than national PAs, and the proportion of threatened non-national PAs is 92.5% in 2020. Thus, future planning and management should place more attention to the non-national PAs that are severely affected by urban expansion. We investigate spatial relation between urban expansion and 2622 protected areas in China. Rapid urban expansion in recent years has posed a serious threat to PAs. Non-national PAs are more severely threatened than the national PAs. [ABSTRACT FROM AUTHOR]

The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP. Reducing PM2.5 air pollution from biomass burning, transport, energy, and manufacturing, in combination with improvements in healthcare, especially in emerging economies like India and China, will be crucial to meeting SDG3.9 [ABSTRACT FROM AUTHOR]

Estimating the health burden of air pollution against the background of population aging is of great significance for achieving the Sustainable Development Goal 3.9 which aims to substantially reduce the deaths and illnesses from air pollution. Here, we estimated spatiotemporal changes in deaths attributable to PM2.5 air pollution in China from 2000 to 2035 and examined the drivers. The results show that from 2019 to 2035, deaths were projected to decease 15.4% (6.6%–20.7%, 95% CI) and 8.4% (0.6%–13.5%) under the SSP1-2.6 and SSP5-8.5 scenario, respectively, but increase 10.4% (5.1%–20.5%) and 18.1% (13.0%–28.3%) under SSP2-4.5 and SSP3-7.0 scenarios. Population aging will be the leading contributor to increased deaths attributable to PM2.5 air pollution, which will counter the positive gains achieved by improvements in air pollution and healthcare. Region-specific measures are required to mitigate the health burden of air pollution and this requires long-term efforts and mutual cooperation among regions in China. Estimating health burden of air pollution against the background of population aging is of significance for achieving Sustainable Development Goal 3.9. Here, the authors show that population aging is expected to be the leading contributor to increased deaths attributable to PM2.5 in China by 2035, which will counter the positive gains achieved by improvements in air pollution and healthcare. [ABSTRACT FROM AUTHOR]

Subgrid data from earth system models are a powerful, yet underutilized, data resource for investigating the climatic impacts of land use and land cover change (LULCC). In this paper, we describe a global dataset on subgrid land surface climate variables produced by the Community Earth System Model in a fully coupled mode. The simulation was conducted at a 0.9° × 1.25° resolution under the Representative Concentration Pathway (RCP) 8.5 scenario from 2015 to 2100. Data are archived for eight subgrid tiles (urban, rural, tree, grass, shrub, bare soil, crop and lake) and include variables on the physical state, surface energy fluxes, runoff and atmospheric forcing conditions. Archival intervals are monthly, daily and hourly. Meta data on land surface parameters are also available. The data files are stored in NetCDF‐4 (Network Common Data Form, version 4) format and the meta data follow the latest Coupled Model Intercomparison Project phase 6 standards. We anticipate that this dataset will become a useful resource for characterizing local climate changes due to LULCC. This dataset can be downloaded from the Harvard Dataverse (https://doi.org/10.7910/DVN/HUXAH6). [ABSTRACT FROM AUTHOR]