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Physical geography focuses on the Earth surface system and is dedicated to revealing how people affect the environment and how the environment reacts to people. Based on its characteristic spatial cognitive perspective, the inductive–deductive combined approach, and the comprehensive research paradigm that integrates multiple elements, processes, and scales, physical geography always provides an important scientific basis for understanding human–nature interactions and solving sustainable development issues in different eras. Putting theory into practice, physical geography plays a pivotal role in realizing the UN Sustainable Development Goals and China's goal of ecological civilization. At present, China is in a stage of rapid socio-economic development and global conditions are changing more quickly than ever. Based on its disciplinary characteristics and traditional advantages, physical geography in China should always develop around social needs and play an increasing role in resource- and environment-related policies and outreach. Future development of physical geography as a discipline in China is expected, taking spatial cognition as the basic perspective and human–nature interaction as the core content, along with the combination of deductive and inductive approaches and the strengthening of interregional integration, all under the goal of sustainability. Considering the shared environmental challenges and the complexity of interconnections between countries in the context of globalization, the academic exploration and practice of physical geography in China have been providing scientific support for the sustainable development of China and beyond. [ABSTRACT FROM AUTHOR]

Abstract China's rapid urbanization has aggravated its air pollution problems and subsequently results in increased interests in the relationship between urbanization and PM 2.5 concentrations. Currently, research on the ways that urbanization directly influences air quality are comparatively mature; however, quantification of the spillover effect of urbanization on PM 2.5 concentrations in adjacent regions remains understudied. Additionally, urbanization is a multi-dimensional phenomena in China and it is important to distinguish the ways in which the multiple aspects of urbanization influence PM 2.5 concentrations. Taking the Beijing-Tianjin-Hebei Urban agglomeration of China as an example, this study explored the spatio-temporal change and spatial dependence pattern of PM 2.5 concentrations, and further examined and compared the unique impacts of the multiple dimensions of urbanization on PM 2.5 concentrations. The results showed that spatial dependence of PM 2.5 generally took place over the range of 200 km in the study area. Economic urbanization had a much stronger influence on air quality than land urbanization or population urbanization; it was determined to be the best indicator to represent the impact of urbanization, especially the spillover effect of urbanization on PM 2.5 concentrations in adjacent regions. Over the period 2000–2010, the impacts from both local and neighboring economic urbanization on PM 2.5 concentrations increased significantly. In contrast, land urbanization mainly exerted influence on air quality in focal regions. Population urbanization showed no significant direct or spillover effects on PM 2.5 concentrations in the whole urban agglomeration. This study provides evidence that the influence of urbanization within and across cities must be considered when conducting joint air pollution control in an urban agglomeration. PM 2.5 taxes based on the diffusion and transfer of environment pressures are one possible policy mechanism that could help to account for the spillover effect of economic urbanization on air quality. System-based approaches and flow-centered governance are two suggested ways to coordinate the management of both urbanization and air quality. Highlights • Spatial dependence of PM 2.5 concentrations occurs over the range of 200 km in BTH. • Spillover effect of urbanization on PM 2.5 occurs through various approaches. • Development of economic, land, population urbanization is inconsistent in BTH. • Economic urbanization can best indicate the impact of urbanization on PM 2.5. [ABSTRACT FROM AUTHOR]

China's rapid urbanization and severe PM 2.5 -dominated air pollution have received worldwide attention. It is important to reveal how urbanization affects the generation of PM 2.5 . A growing amount of research has examined the local urbanization impact on PM 2.5 concentrations. However, few studies have quantified the influence of neighboring urbanization in terms of the spatial dependence of PM 2.5 concentrations. Some studies considered these spatial effects but overlooked the natural controlling factors. In a comparative view among Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations in China during 2000–2010, the direct and spillover effects of urbanization on PM 2.5 concentrations were explored using spatial regression models that set urbanization and natural indicators as core and controlling variables, respectively. The results showed natural controlling factors were statistically significant; their inclusion in the regression model improved the reliability of estimation. It was also found that the spillover effect of urbanization substantially contributed to the spatial dependence of PM 2.5 concentrations. Nevertheless, the direct and spillover effects of urbanization on PM 2.5 concentrations differed among urban agglomerations and changed over time due to the complexity of urbanization processes. For the Beijing-Tianjin-Hebei urban agglomeration in 2010, the direct effect showed that the urban PM 2.5 concentration increased by 0.138% averagely for every 1% increase of the urbanization level. Likewise, the spillover effect showed that urban PM 2.5 concentration increased by 0.340% for every 1% increase in the average urbanization level of its neighboring cities. In addition, the conflict between PM 2.5 abatement and urbanization level development in the three urban agglomerations was alleviated after 2007, reflected by the simultaneous improvement of urbanization level, urban air quality, and urbanization quality (the ratio of urbanization level to urban air pollution). This study provides policy makers with more detailed characterization about the impact of urbanization on PM 2.5 concentrations, and it is suggested that not only the direct effect but also the spillover effect should be taken into account in guiding air pollution control of urban agglomerations. [ABSTRACT FROM AUTHOR]

Increasingly growing consumption-based water use (WU) combined with climate change have exacerbated water stress globally and regionally, yet little is known about how the WU change is affected by metacoupled processes which involve human-nature interactions across space; within and across adjacent and distant places. This study aims to unveil the spatio-temporal pattern of China's WUs during 2007–2015 and its underlying local and non-local drivers. Results show that China's total WU exhibited an upward trend from 386.7 billion m³; in 2007 to 431.2 billion m³ in 2012 but dropped to 412.6 billion m³ by 2015. Widespread and continuous water use efficiency improvement contributed most to offsetting the increase in WU driven by the rising affluence and growing population in the context of rapid urbanization and industrialization. Economic structure drove a relatively large WU reduction (responsible for −23.7% of the WU change during 2007–2015), in line with China's ongoing transform from a capital investment-driven economy to a consumption-driven one and decoupling economic growth from environmental pressure. The population share representing the non-local factor of migration effect was large enough to be seen clearly in the changing WUs across China: the WUs of coastal areas ascended while inland areas descended, which was in accordance with migration patterns. Our findings could make a valuable contribution to decision-making in identifying hotspot areas, charting systematic courses for sustainable water use, and combining demand-oriented and supply-oriented measures. [Display omitted] • National WU decreased under the policy intervention in China. • Migration effect is identified to indicate the non-local factors affected WU trends. • The largest per capital WUs were found in low developed provinces. • WUs in less developed areas were more driven by capital investment than consumption. • Decline in WU intensity partially leads to the decoupling of WU and GDP. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vegetation coverage increased along with urbanization in PRD during 2000–2012. • Relationship between vegetation and urbanization varied at 1−20 km scales. • Mean local variance was used to identify appropriate analysis scale. • NTL-LAI appropriate analysis scale was mainly affected by urbanization level. Accurate quantification of the relationship between urbanization level and vegetation coverage can provide scientific support for urban sustainable development. However, the interaction between them across multi-scales is under-researched because of its complexity. Based on climate change (i.e. precipitation, temperature and solar radiation), partial correlation relationship between urbanization level (nighttime light, NTL) and vegetation coverage (leaf area index, LAI) at different scales (1–20 km) in the Pearl River Delta (PRD) was explored. Mean local variance was used to determine the appropriate scale of the relationship, at which these metrics could have the minimum information missing. The consistency in appropriate analysis scales of NTL, LAI, and NTL-LAI, was quantified to identify which factor more influenced the appropriate analysis scale of NTL-LAI correlation. The results showed from 2000 to 2012, the urbanization level increased at the rate of 0.58/yr and the average LAI increased slowly at the rate of 0.02 m2/m2/yr. The partial correlation between NTL and LAI depicted that urbanization promoted vegetation coverage in the PRD. Meanwhile, the appropriate analysis scale of NTL-LAI correlation was more determined by the analysis scale of urbanization level, than that of vegetation coverage. This study revealed the scale effect of the relationship between urbanization level and vegetation coverage, and identified the determine factor of appropriate analysis scale of the relationship, which could help for the scale selection in related studies. [ABSTRACT FROM AUTHOR]

Irrigated agriculture has had an enormous influence on food security, water security and human well-being. Water footprint (how much water is used), water scarcity (how scarce water is), and crop water productivity (how much productivity irrigation adds) are important indicators for evaluating sustainability in irrigated agriculture. Yet these interrelated indicators have not been studied simultaneously at the county level – the basic administrative unit of agricultural planning and water management in countries such as China, India and Japan. To fill this knowledge gap, we performed a demonstration in China's major crop production region, the North China Plain (NCP)'s 207 counties from 1986 to 2010. The results show that the irrigated agriculture's annual water footprint in the North China Plain increased from 53 billion m3 in 1986 to 78 billion m3 in 2010. All counties faced water scarcity during 1986-2010 even as the average crop water productivity increased from 0.90 kg m−3 to 1.94 kg m−3. There are 173 NCP counties suffering severe water scarcity but still producing significant crop yield with a high water footprint, a red flag of unsustainable irrigated agriculture. This study has implications for revealing potential unsustainable conditions in irrigated agriculture worldwide. • Annual water footprint from irrigated agriculture in the whole North China Plain (207 counties) increased over time. • All counties in the North China Plain faced severe water scarcity. • Spatial-temporal dynamic of crop water productivity in 207 counties was calculated. • We developed water consumption method for calculating water footprint. [ABSTRACT FROM AUTHOR]