China's response to a national land-system sustainability emergency.

China has responded to a national land-system sustainability emergency via an integrated portfolio of large-scale programmes. Here we review 16 sustainability programmes, which invested US$378.5 billion (in 2015 US$), covered 623.9 million hectares of land and involved over 500 million people, mostly since 1998. We find overwhelmingly that the interventions improved the sustainability of China's rural land systems, but the impacts are nuanced and adverse outcomes have occurred. We identify some key characteristics of programme success, potential risks to their durability, and future research needs. We suggest directions for China and other nations as they progress towards the Sustainable Development Goals of the United Nations' Agenda 2030.

Reexamining the relationship between urbanization and pollutant emissions in China based on the STIRPAT model.

Understanding the relationship between urbanization and pollutant emissions in China is of great significance to realizing sustainable development. Previous studies focused on the relationship between urbanization and air pollutants in China. However, the relationship between urbanization and industrial or domestic pollutants remains unclear. In this paper, we used the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to examine whether an environmental Kuznets curve (EKC) relationship exists between urbanization and pollutant emissions, including industrial wastewater, industrial SO2, industrial soot (dust), and domestic garbage based on panel data for 277 prefecture-level cities in China from 2003 to 2015. We found that industrial soot (dust) emissions and domestic garbage increased by 83.0% and 43.5%, respectively, whereas industrial wastewater discharge and SO2 emissions decreased by 7.4% and 10.5%, respectively. The identified inverted U-shaped relationship between the urbanization ratio (i.e., percentage of the population living in urban areas) and industrial pollutants supports the EKC hypothesis. However, the domestic garbage volume increased with increasing urbanization ratio. In the future, more attention should be paid to the prevention and control of domestic pollution. In addition, small and medium-sized cities should reduce pollutant emissions and determine effective ways to achieve sustainable development.

Substantially reducing global PM2.5-related deaths under SDG3.9 requires better air pollution control and healthcare.

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.

Relationships between urban expansion and socioenvironmental indicators across multiple scales of watersheds: a case study among watersheds running through China.

Understanding the relationships between urban expansion and social/environmental features is fundamental to managing watershed and urban expansion. However, such relationships remain unclear, especially across multiple scales of watersheds. Here, we quantified the correlation between urban expansion measures and 255 socioenvironmental indicators across three scales of watersheds running through China (20, 103, and 349 watersheds) during 1992-2016 and analyzed their scaling relations. The results showed that the number of indicators showing a significant correlation with the area and speed of urban expansion increased from 132 and 153 to 234 and 237, respectively, from level 1 to level 3 watersheds. Among these indicators, urban expansion was significantly correlated with indicators of climate and anthropogenic impact. From a large scale (level 1 watershed) to a small scale (level 3 watershed), 104 and 84 socioenvironmental indicators shifted from uncorrelated to significantly correlated with urban expansion area and speed. The constraint line analysis further confirmed that some relationships were nonlinear, which suggested that the drivers and impacts of urban expansion have scaling effects. We argue that it is crucial to consider the scaling effects of urban expansion when we formulate urban or watershed management plans.

The challenge of population aging for mitigating deaths from PM2.5 air pollution in China.

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.

Developing a method for assessing environmental sustainability based on the Google Earth Engine platform.

Environmental sustainability is the foundation and of great significance for the sustainable development of urban agglomerations. Taking the Beijing-Tianjin-Hebei urban agglomeration as an example, we developed a method to effectively assess long-term regional environmental sustainability based on the Google Earth Engine (GEE) platform. We used the GEE to obtain 5206 Landsat remote sensing images in the region from 1983 to 2016 and developed the comprehensive environmental index (CEI) to assess regional environmental sustainability based on the theme-oriented framework proposed by the United Nations Commission on Sustainable Development. We found that the environmental sustainability of the urban agglomeration showed a trend of first rising, then falling, and then rising again in the past 30 years. The average CEI increased from 0.621 to 0.631 from 1985 to 1990, dropped to the lowest value of 0.618 in 2000, and then rose to the highest value of 0.672 in 2015. In particular, the extent of areas in which environmental sustainability improved (56% of the region) was greater than the extent of areas in which environmental deterioration occurred. The environmental sustainability of Hengshui, Xingtai, and Cangzhou in the southeast of the region has been significantly improved. The method proposed in this study provides an automatic, rapid, and extensible way to assess regional environmental sustainability and provides a scientific reference for improving the sustainability of the regional environment.

Updating global urbanization projections under the Shared Socioeconomic Pathways.

Urbanization level is an important indicator of socioeconomic development, and projecting its dynamics is fundamental for studies related to global socioeconomic and climate change. This paper aims to update the projections of global urbanization from 2015 to 2100 under the Shared Socioeconomic Pathways by using the logistic fitting model and iteratively identifying reference countries. Based on historical urbanization level database from the World Urbanization Prospects, projected urbanization levels and uncertainties are provided for 204 countries and areas every five years. The 2010-2100 year-by-year projected urbanization levels and uncertainties based on the annual historical data from the World Bank (WB) for 188 of countries and areas are also provided. The projections based on the two datasets were compared and the latter were validated using the historical values of the WB for the years 2010-2018. The updated dataset of urbanization level is relevant for understanding future socioeconomic development, its implications for climate change and policy planning.

The growth mode of built-up land in floodplains and its impacts on flood vulnerability.

Built-up land in floodplains (BLF) is a vital indicator of the socio-hydrological system, and its dynamics are key to understanding and managing flood risk. However, previous studies have neglected the impacts of BLF growth modes (e.g., patch sizes and expansion types) on flood vulnerability. This paper fills this gap by assessing the BLF's growth modes and revealing their divergent impacts on flood vulnerability using a case study in the Yangtze River Economic Belt (YREB), China. The results show that the BLF has nearly doubled in the YREB during 1990-2014. A considerable proportion (35.43%) of the BLF growth is scattered in small patches (≤1 km2), which have a much stronger correlation with flood occurrence than that of the other patch sizes. In terms of expansion types, the edge-expansion type dominates 57.52% of the BLF growth, followed by the leapfrogging and infilling expansions. Both the leapfrogging and the edge-expanding BLFs are significantly associated with flood occurrence, while the infilling type is not. The patch size and expansion type can thus influence the vulnerability of BLF patches, which is also supported by real-world cases. These findings enrich a general understanding of BLF growth and its impacts on flood vulnerability. The scientific community and policymakers should pay attention to not only the quantity of BLF growth, but also its spatial arrangement.

Stronger policy required to substantially reduce deaths from PM2.5 pollution in China.

Air pollution kills nearly 1 million people per year in China. In response, the Chinese government implemented the Air Pollution Prevention and Control Action Plan (APPCAP) from 2013 to 2017 which had a significant impact on reducing PM2.5 concentration. However, the health benefits of the APPCAP are not well understood. Here we examine the spatiotemporal dynamics of annual deaths attributable to PM2.5 pollution (DAPP) in China and the contribution from the APPCAP using decomposition analysis. Despite a 36.1% increase in DAPP from 2000 to 2017, The APPCAP-induced improvement in air quality achieved substantial health benefits, with the DAPP in 2017 reduced by 64 thousand (6.8%) compared to 2013. However, the policy is unlikely to result in further major reductions in DAPP and more ambitious policies are required to reduce the health impacts of air pollution by 2030 and meet the United Nation's Sustainable Development Goal 3.

Rapid Population Growth throughout Asia's Earthquake-Prone Areas: A Multiscale Analysis.

Assessing the changes of the population living throughout the most seismically hazardous area (MSHA) constitutes an important foundation for seismic risk assessment. However, the changes of the population living in the MSHA of Asia, which exhibits the highest number of earthquake related fatalities, were poorly understood. Therefore, this study analyzed the changes of the population in the MSHA between 2000 and 2015 at the continental, subcontinental, and national scales. We found that the population, especially the vulnerable population (i.e., children under or equal to the age of 14 and elderly people over or equal to the age of 65), in Asia's MSHA increased rapidly between 2000 and 2015. The population in the MSHA increased by 185.88 million with a growth rate of 20.93%, which was 3.38% greater than that in the non-MSHA region. Meanwhile, the vulnerable population in the MSHA increased by 63.65 million with a growth rate of 19.73%. The increase of the vulnerable population in the MSHA was 19.93% greater than that in the non-MSHA region. We also found that urban population growth was a major factor impacting the increase in both the population and the vulnerable population throughout Asia's MSHA. Therefore, attention should be paid to the changes of the population in Asia's MSHA, whilst it is imperative to execute strict building codes and select the development location more carefully in the MSHA.

Rapid Population Growth in Chinese Floodplains from 1990 to 2015.

Although China suffers from frequent and disastrous floods, the spatiotemporal pattern of its population living in the floodplain (PopF) is still unknown. This strongly limits our understanding of flood risk and the effectiveness of mitigation efforts. Here we present the first quantification of Chinese PopF and its dynamics, based on newly-available population datasets for years 1990, 2000, 2010, and 2015 and on a flood map. We found that the PopF in 2015 was 453.3 million and accounted for 33.0% of the total population, with a population density 3.6 times higher than outside floodplains. From 1990 to 2015, the PopF increased by 1.3% annually, overwhelmingly faster than elsewhere (0.5%). A rising proportion (from 53.2% in 1990 to 55.6% in 2015) of the PopF resided in flood zones deeper than 2 m. Moreover, the PopF is expected to increase rapidly in the coming decades. We also found the effect of flood memory on controlling PopF growth and its decay over time. These findings imply an exacerbating flood risk in China, which is concerning in the light of climate change and rapid socioeconomic development.

Alternative future analysis for assessing the potential impact of climate change on urban landscape dynamics.

Assessing the impact of climate change on urban landscape dynamics (ULD) is the foundation for adapting to climate change and maintaining urban landscape sustainability. This paper demonstrates an alternative future analysis by coupling a system dynamics (SD) and a cellular automata (CA) model. The potential impact of different climate change scenarios on ULD from 2009 to 2030 was simulated and evaluated in the Beijing-Tianjin-Tangshan megalopolis cluster area (BTT-MCA). The results suggested that the integrated model, which combines the advantages of the SD and CA model, has the strengths of spatial quantification and flexibility. Meanwhile, the results showed that the influence of climate change would become more severe over time. In 2030, the potential urban area affected by climate change will be 343.60-1260.66 km(2) (5.55 -20.37 % of the total urban area, projected by the no-climate-change-effect scenario). Therefore, the effects of climate change should not be neglected when designing and managing urban landscape.