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Industrial production is key to economic development, yet it significantly influences the water environment. Recent literature has mainly focused on economic development and water pollution separately, lacking an integrated assessment. This study aims to clarify the links between industrial production and water pollution and its driving factors in the Yangtze River Economic Belt (YREB) in 2012–2017 based on environmentally-extended input-output analysis and structural decomposition analysis, thus identifying key regions and sectors for pollution reduction. The results revealed that manufacture of foods and tobacco (MFT) and chemical industry (CI) in Anhui, Jiangsu, Jiangxi, Hunan, and processing of petroleum, coking, processing of nuclear fuel (PPCN) in Chongqing were the primary sources of total chemical oxygen demand (COD), ammoniacal nitrogen (NH 3 –N), total nitrogen (TN), and total phosphorus (TP) discharges. The structural decomposition analysis (SDA) results demonstrated that the discharge intensity effect caused a decrease of 7.91 Mt, 0.22 Mt, 0.25 Mt, and 0.03 Mt of the indirect COD, NH 3 –N, TN, and TP discharge, while the scale effect led to an increase of 1.95 Mt, 0.26 Mt, 0.24 Mt and 0.03 Mt of them in 2012–2017. According to the analysis, water pollution reduction and industrial structure modernization are needed in the YREB. The technological upgrading of highly polluting industries and the structural adjustment between traditional highly polluting industries and high-tech industries were the focus for achieving green development of the YREB, especially in Anhui, Hubei, Guizhou and Yunnan. The establishment of green industrial parks, the development of environmental regulations, and the implementation of supply-side reform policies can benefit water pollution reduction and sustainable development. [Display omitted] • The EEIO model was applied to identify key regions and sectors for water pollution. • MFT, MT, MTCS, PPCN and CI were major sectors for water pollutant discharges. • Jiangsu and Jiangxi were major contributors for water pollutant discharges. • Discharge intensity effect decrease water pollution, scale effect did the opposite. • Green development need focus on industries with high indirect pollutant discharge. [ABSTRACT FROM AUTHOR]

Global mitigation of greenhouse gas (GHG) emission targets to regional solution at different scales with structural effects. Because local ecosystem service has different functions to influence regional environment, it is unclear that land use structural effects on lowering emission intensity and mitigating air pollution, and it is debatable that the efficiency of mitigation of GHG emission can be improved by increasing what kind of ecological infrastructure at regional scale. We propose a systematic methodology on identification of trade-offs among structural impacts of land use change on emission intensity at regional scale through both qualitatively and quantitatively statistical analysis to clarify impacts of different land use on the mitigation of emission intensity. In particular to a region with some distinct constraints of natural resources, regional planning has to rely on scientific solutions for bridging the gap of emission mitigation target among multi-levels of administrations and at same time enhancing the optimal allocation of natural resource. In this case study, we qualitatively analyze the principle component among impact factors in a regional socio-economic-ecological system of Zhangye City (where is located at the middle reach of the Heihe River Basin) during 1980s–2010s, and quantitatively analyze the relationship between land use structure and emission intensity with controlling the effects of air contaminations. The analytical results prove that forest land has statistically significant impacts on the mitigation of emission intensity, more importantly, there are no statistical significant evidences showing that cultivated land and wetland have the same functions. It indicates that to identify key issues from those mixed impacts of land use structure at regional scale determines to promote an optimal path of natural resource allocation for reducing the GHG emission and air contaminations. It implies that mitigation of GHG sorely needs to take land use structure changes into consideration of the systematic research for scientifically improving regional planning and sustainable development. [ABSTRACT FROM AUTHOR]

The article examines the rationale, challenges and opportunities of promoting urbanization in Western China. Topics covered include the launch of the National Western Development Strategies in 1999, trends in urbanization in China since 1978, and the benefits of urbanization like the promotion of social, economic, environmental and natural capital. Also discussed are the challenges to be considered in promoting urbanization in the western region, including the fragile ecological system.

After one decade of development, the methods to explore the temporal and spatial process of LUCC (Land Use and Land Cover Change) have been vastly improved; and in some sense a methodology framework used to study the temporal and spatial process is being rapidly developed. The methodology framework is based on the integration of the classical theories of Geography and the recent developed technologies of remote sensing and GIS, which is a new research field to meet the need for scientific information to promote the studies on global change adaptation and sustainable development. It addressed the following: the detection and description of the temporal and spatial process of LUCC, analysis of driving mechanism of LUCC, simulation of LUCC process and evaluation of ecological effect due to LUCC. The formation of methodology framework to study the temporal and spatial process of LUCC, to some extent, has been promoted to tackle the hard-nut topics in science through interdisciplinary efforts among geography, GIS and macro-ecology. The domestic and overseas research trends indicate that the development of detection and analytical technologies of remote sensing information and the methodological innovation of simulating the temporal and spatial process of LUCC, play an important role in promoting the development of methodology framework of the temporal and spatial process of LUCC. The synthetic application of the detection and analytical technologies of LUCC remote sensing information, the construction of multi-source and temporal-spatial data platform and the realization of massive data availability and integration are all kernel components of the methodology framework of the temporal and spatial process of LUCC. We can expect that the research methods system of the temporal and spatial process of LUCC will play a more important role in guiding the research activities of LUCC processes at regional and global levels. [ABSTRACT FROM AUTHOR]

• The ESAP model was used to calculate land and agriculture productivity across China. • The agricultural productivity of municipal areas across China was updated for the period between 2010 and 2014. • Patterns in agricultural productivity spatiotemporal differentiation across China were obvious. • Data showed a strong positive spatial correlation between the agricultural productivity of municipal administrative areas. Understanding spatiotemporal patterns in Chinese agriculture is extremely important for national sustainable development. We apply the Estimation System of Agricultural Productivity (ESAP) model in this study to calculate this variable across China between 2004 and 2014 and further analyze spatiotemporal patterns at the municipal level using Moran's I and Local Indicators of Spatial Association (LISA) indices. The results of this study reveal that input factors have been dynamically embedded within this system and can therefore be utilized to avoid overestimates of agricultural productivity via the ESAP model, while the dependence of productivity on climatic factors also determines inter-annual variability and spatial patterns. The results of this analysis show that average agricultural productivity has tended to decrease spatially from south-to-north and from east-to-west across China, while generally increasing temporally between 2004 and 2014. The data presented in this study reveal a strong positive spatial correlation between values for agricultural productivity in municipal administrative areas, to the extent that identified LISA agglomeration types can mostly be categorized as either "high-high" (HH) or "low-low" (LL). [ABSTRACT FROM AUTHOR]

Highlights • Our RS-based method integrates 11 dimensional features to map urban land use. • We develop multi-dimensional DPSIR-based indicators to analyze urban land expansion. • Increasing sprawl while decreasing density reduces economic-socio-ecological benefits. • Quantifying the interactions between multiple indicators can aid urban planning. • Optimizing multi-dimensional trade-offs and synergies is the key to sustainability. Abstract Rapid urban land expansion not only stimulates socioeconomic development, but can lead to negative impacts that threaten regional food security, ecological construction, and sustainable urban development, including losses of cropland and habitats, the creation of housing bubbles, and reductions in biodiversity. Because these economic-socio-ecological problems are generally more serious in ecologically fragile areas, this study focuses on trends seen in Ganzhou District, a typical oasis city within the Heihe River Basin (HRB) in an arid-to-semi-arid area of China. We apply a remote-sensing (RS)-based method that incorporates 11 dimensional features of Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images to map changes in urban land, and also develop a series of multi-dimensional indicators within a drivers, pressures, states, impacts, and responses (DPSIR) framework to quantify urban land expansion. The results of this study show that the urban land area of Ganzhou District in 2016 had expanded by 394.43% from 1987 levels, from 1979.64 ha to 9787.86 ha. These increasing pressures, jointly driven by gross domestic product (GDP), urban population, cropland area, and the industrial structure indicator (ISI), have led to the worsening economic-socio-ecological states and impacts of urban land expansion. Specifically, between 1987 and 2016, expansion intensity (EIPI) and expansion rate pressure indicators (ERPI) increased from 60.27 ha/a to 520.88 ha/a, and from 3.04%/a to 10.21%/a, respectively. Thus, the state indicators of economic development (EDSI), population carrying capacity (FDSI), food security (FSSI), and ecological construction (ECSI) decreased by 2.21 × 103 USD/ha, 17.62 population/ha, 34.20, and 10.80, respectively. Moreover, the impact indicators of economic development (EDII), population carrying capacity (FDII), and food security (FSII) decreased by 150.68 × 103 USD/ha, 62.12 population/ha, and 27.31, respectively, while the ecological construction impact indicator (ECII) increased by 29.39 between 1997 and 2007 and decreased by 13.31 between 2007 and 2016. Data also show that the area and proportion of cropland and ecological land occupied by urban land expansion increased over time. We therefore propose a series of economic-socio-ecological responses to help limit urban sprawl and foster compact green cities. Measures include planning urban growth boundaries, revitalizing urban centers and brownfields, using and re-using urban land more efficiently, strengthening land regulations, curbing excessive cropland expansion, cultivating more urban green spaces, and optimizing the trade-offs and synergies between multiple conflicting dimensions. [ABSTRACT FROM AUTHOR]

Water and land (W-L) resources become even more important in the context of urban-rural integration in China's arid northwest region in order to achieve sustainable development goals (SDGs). Our study used Gini coefficients to examine the relationship between natural resources and economic development in China's Xinjiang Uygur Autonomous Region. Cobb-Douglas (C-D) production functions were used to determine the economic impacts of W-L resources on rural-urban economic development. We also examined the spatiotemporal interaction characteristics of the growth drag effect of W-L resources. As a result of the decline in Gini coefficients between 2000 and 2020, Xinjiang experienced a decrease in water resources, land resources, and urban-rural GDP (gross domestic product). The output elasticities of urban-rural land and water resources were 0.3544 and 0.4790, respectively, whereas the output elasticities of urban-rural land resources were 0.1501 and 0.2185, respectively. As a result, water resources contribute to the growth of urban-rural GDP more than land resources, and W-L resources contribute to the economic development of rural areas more than it does to that of urban areas. Land resources were found to have a drag effect on urban and rural economies, respectively, in 7 and 56 counties, respectively, and water resources were found to have a drag effect on urban and rural economies, respectively, in 67 and 58 counties. In Xinjiang, water resources contributed more to economic growth than land resources. Even though W-L resources still have a drag effect on urban-rural economic growth, we can gain greater driving force by optimizing and improving resource use. However, this requires an optimal allocation and efficient use of water resources. • The drag model can analyze the drag effects of natural resource use on the urban-rural economy. • Water resources are more compatible with the urban-rural economy than land resources. • Water constraints affect Xinjiang's economic growth more than land constraints. • Water scarcity reduced Xinjiang's urban economic growth by 0.68%–1.57% from 2000 to 2020. [ABSTRACT FROM AUTHOR]

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China. [ABSTRACT FROM AUTHOR]

Clarifying the interactive relationship between urban land-use efficiency (ULUE), industrial transformation, and carbon emissions is of great realistic significance for promoting the coordination of 'resources-economy-environment' and achieving green development. This study used the stochastic frontier analysis (SFA), index method (IM), and remote sensing inversion to calculate the ULUE, the industrial transformation degree (ITD), and the carbon emission intensity (CEI) for 108 cities in the Yangtze River Economic Belt (YREB) from 2005 to 2017, and analyzed their spatiotemporal evolution characteristics. The generalized method of moments (GMM) and impulse response function (IRF) in the panel vector autoregressive (PVAR) model are used to empirically test the dynamic interactive effects of ULUE, ITD, and CEI. The empirical results show that: (i) During the study period, the ULUE and ITD of the YREB increased year-by-year, showing the pattern characteristics of high in the east and low in the west. The CEI decreased by 50.20% cumulatively, and the low-value areas spread from the center of the urban agglomeration towards the periphery. (ⅱ) The GMM shows that there is a significant dynamic dependence between the ULUE, ITD, and CEI. The ULUE has a positive driving effect on the industrial transformation and a negative effects on the CEI in the short term. (ⅲ) The IRF shows that the ULUE and industrial transformation show a synergistic effect of interactive growth. The improvement of the ULUE and industrial restructuring will force the reduction of CEI. The article proposes that the city should take the new urbanization path of resource-conserving, cost-effective, and environment-friendly. • The paper depicted the spatiotemporal patterns for ULUE, ITD, and CEI in the YREB. • The dynamic interactive effects of the ULUE, ITD, and CEI are revealed. • The ULUE has negative influence on CEI. • The ULUE and ITD show a synergistic effect of interactive growth. • The improvement of the ULUE and ITD jointly form a carbon reduction mechanism. [ABSTRACT FROM AUTHOR]

• Distribution effect of carbon-food nexus for Chinese cities were explored. • Several methods built using the spatial decoupling index were proposed. • Chinese cities exhibited varying degrees of the distribution effect over the period. • Driver pattern of carbon-food nexus has changed over the years. Climate change mitigation and food security are sustainable development goals (SDGs) of the United Nations. Despite extensive studies focused on the nexus of different SDGs and corresponding mechanisms, the distribution effect of carbon-food nexus and its driver has received limited attention, hindering policy making for balancing pathways of regional emission reduction and food production improvement. The present study explored the distribution effect (i.e., spatial performance) of carbon-food nexus from multiple perspectives (namely, status quo, drivers, and trend) based on a unique city-level dataset from 2005 to 2017. To this end, we proposed the spatial decoupling index, the corresponding decomposition and nonparametric models for capturing the multi-perspective distribution effects. The results indicated that Chinese cities, categorized by population scale and economic structure, exhibited varying degrees of distributions of carbon-food nexus over the period. Moreover, the driver pattern of carbon-food nexus was noted to have changed, wherein investment efficiency and scale were positive drivers. Furthermore, we showed that a more developed city's economy was statistically significantly associated with higher carbon emission and lower food production. Therefore, related stakeholders should take more actions such as strengthening capital accumulation and joint management of carbon intensity, for improving the distribution effect of the overall city-level carbon-food nexus. [ABSTRACT FROM AUTHOR]