Managing urban development could halve nitrogen pollution in China

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on

The Production–Living–Ecological Land Classification System and Its Characteristics in the Hilly Area of Sichuan Province, Southwest China Based on Identification of the Main Functions

Production–living–ecological land (PLEL) is one of the research focuses of land planning and regional sustainable development in China. This paper builds a three-level classification system of PLEL based on the identification of the main land use functions (LUFs). Taking 215 typical towns in the hilly area of Sichuan Province, Southwest China as samples, the quantitative, spatial, and functional characteristics and impact factors of PLEL were studied. The results showed that (1) production land holds a dominant role in the hilly area of Sichuan Province, and production land (PL), living land (LL) and ecological land (EL) account for 66.06%, 7.60%, and 26.34% of the area, respectively. The area of agricultural production land is the largest; forestland and rural living land rank second and third. (2) The spatial patterns of PLEL in different regions of hilly area have differences. The proportion of PL gradually decreases from north to south, while the proportion of EL gradually increases from north to south, and the difference in LL is not obvious. The EL is mainly distributed in the upper and middle parts of hills, and the PL and LL are mainly distributed in the foot slopes and valleys. (3) The main functions of PLEL in the hilly area of Sichuan are production and ecology. The production function is mainly for agricultural and forestry products, and the living function is mainly for cultural leisure and residential functions. There are little differences among the ecological sub-functions. (4) There is a strong correlation between PLEL and natural–social–economic factors in the hilly area of Sichuan. Natural conditions such as latitude, relative height, and surface roughness have significant impacts on PL and EL. Social and economic factors such as population density, location and total industrial output value have a significant impact on LL. The results of this study provide valuable implications for the spatial planning and sustainable development in the Sichuan Basin and upstream of the Yangtze River

Temporal-Spatial Variations and Regional Disparities in Land-Use Efficiency, and the Response to Demographic Transition

China has undergone rapid industrialization and urbanization over the past 40 years. In this process, as a large country with a vast territory and a large population, China’s population development and land utilization have been greatly affected and undergone dramatic changes. In this paper, we mainly discuss the temporal and spatial variation characteristics of land-use efficiency in China from 1991 to 2016 and the regional disparities and explore the impacts of demographic transition on land-use efficiency by employing a STIRPAT model. In terms of space, China’s land-use efficiency has significant agglomeration distribution characteristics and regional inequality, and the degrees of agglomeration and differentiation have gradually become enhanced over time. Our study on the influences of demographic transition on land-use efficiency found a Kuznets curve relationship between the transition of population size and land-use efficiency, as well as between the income level transition and land-use efficiency. Especially, land-use efficiency first increases up to the population threshold of 10,611.877 × 104, then efficiency decreases as the population grows. The overall average population in the whole country is 4117.753 × 104, which is smaller than the identified threshold. Interestingly, the factors influencing land-use efficiency also showed very significant regional disparities. In the eastern region, there is a U-curve relationship between the population employed in secondary industries (ES2) and land-use efficiency. Land-use efficiency decreases down to the ES2 threshold of 343.674 × 104 for the eastern region, whereas the overall average ES2 is 874.976 × 104, indicating that this region has reached the turning point where land-use efficiency will improve as the population employed in secondary industries increases. Meanwhile, the increase in the human capital level was significantly positively correlated with land-use efficiency in the eastern region. For the central region, the transition of the urban–rural population structure (measured by the urbanization rate) significantly increased land-use efficiency. In addition, the results of panel estimation showed a Kuznets relationship between the population employed in tertiary industries (ES3) and land-use efficiency in the western region. Land-use efficiency increases up to the ES3 threshold of 455.545 × 104, and then decreases with an increasing population employed in tertiary industries, whereas the overall average ES3 in the western region is 415.97 × 104, which is smaller than the identified threshold. Policymakers could use these findings to inform rational suggestions with a sound scientific basis regarding the promotion of land-use transition

Is Big Good or Bad?: Testing the Performance of Urban Growth Cellular Automata Simulation at Different Spatial Extents

The accurate prediction of urban growth is pivotal for managing urbanization, especially in fast-urbanizing countries. For this purpose, cellular automata-based (CA) simulation tools have been widely developed and applied. Previous studies have extensively discussed various model building and calibration techniques to improve simulation performance. However, it has been a common practice that the simulation is conducted at and only at the spatial extent where the results are needed, while as we know, urban development in one place can also be influenced by the situations in the broader contexts. To tackle this gap, in this paper, the impact of the simulation of spatial extent on simulation performance is tested and discussed. We used five villages at the rural⁻urban fringe in Chengdu, China as the case study. Urban growth CA models are built and trained at the spatial extent of the village and the whole city. Comparisons between the simulation results and the actual urban growth in the study area from 2005 to 2015 show that the accuracy of the city model was 7.33% higher than the village model and the latter had more errors in simulating the growth of small clusters. Our experiment suggests that, at least in some cases, urban growth modeling at a larger spatial extent can yield better results than merely modeling the area of interest, and the impacts of the spatial extent of simulation should be considered by modelers

The Dual Roles of Nano Zero-Valent Iron and Zinc Oxide in Antibiotics Resistance Genes (ARGs) Spread in Sediment

Nanoparticles (NPs) are widely used and ubiquitous in the environment, but the consequences of their release into the environment on antibiotics resistance genes (ARGs), microbial abundance, and community, are largely unknown. Therefore, this study examined the effect of nano zero-valent iron (nZVI) and zinc oxide (nZnO) on tetracycline resistance genes (tet-ARGs) and class 1 integron (intI1) in sediment under laboratory incubation. The coexistence of NPs and tetracycline (TC) on tet-ARGs/intI1 was also investigated. It was found that nZVI and nZnO promoted tet-ARGs/intI1 abundance in sediment without TC but reduced the inducing effect of TC on tet-ARGs/intI1 in sediment overlaid with TC solution. Without TC, nZVI, intI1, and the bacterial community could directly promote tet-ARGs spread in nZVI sediment, while intI1 and bacterial abundance were the most directly important reasons for tet-ARGs spread in nZnO sediment. With TC, nZVI and bacterial community could reduce tet-ARGs abundance in nZVI sediment, while nZnO and bacterial community could directly promote tet-ARGs in nZnO sediment. Finally, these findings provided valuable information for understanding the role of NPs in promoting and reducing ARGs in the environment

Spatially Explicit Reconstruction of Cropland Using the Random Forest: A Case Study of the Tuojiang River Basin, China from 1911 to 2010

A long-term, high-resolution cropland dataset plays an essential part in accurately and systematically understanding the mechanisms that drive cropland change and its effect on biogeochemical processes. However, current widely used spatially explicit cropland databases are developed according to a simple downscaling model and are associated with low resolution. By combining historical county-level cropland archive data with natural and anthropogenic variables, we developed a random forest model to spatialize the cropland distribution in the Tuojiang River Basin (TRB) during 1911–2010, using a resolution of 30 m. The reconstruction results showed that the cropland in the TRB increased from 1.13 × 104 km2 in 1911 to 1.81 × 104 km2. In comparison with satellite-based data for 1980, the reconstructed dataset approximated the remotely sensed cropland distribution. Our cropland map could capture cropland distribution details better than three widely used public cropland datasets, due to its high spatial heterogeneity and improved spatial resolution. The most critical factors driving the distribution of TRB cropland include nearby-cropland, elevation, and climatic conditions. This newly reconstructed cropland dataset can be used for long-term, accurate regional ecological simulation, and future policymaking. This novel reconstruction approach has the potential to be applied to other land use and cover types via its flexible framework and modifiable parameters

Construction of a Territorial Space Classification System Based on Spatiotemporal Heterogeneity of Land Use and Its Superior Territorial Space Functions and Their Dynamic Coupling: Case Study on Qionglai City of Sichuan Province, China

Territorial space classification (TSC) provides the basis for establishing systems of national territory spatial planning (NTSP) and supervising their implementation in China, thus has important theoretical and application significance. Most of the current TSC research is related to land use/land cover classification, ignoring the connection of the NTSP policies and systems, failing to consider the spatiotemporal heterogeneity of land use superior territorial space functions (TSFs) and the dynamic coupling between land use and its superior TSFs on the result of TSC. In this study, we integrated the factors influencing the connection of NTSP policies and systems and established a theoretical framework system of TSC from the perspective of spatial form and functional use. By integrating the q-statistic method with spatiotemporal geographical analysis, we propose a method to construct a TSC system for Qionglai City of Sichuan Province in China based on the spatiotemporal heterogeneity of land use superior TSFs and the dynamic coupling between land use and its superior TSFs. It makes up for the deficiency of directly taking land use/land cover classification as TSC and solves the problems of ignoring the spatiotemporal heterogeneity of land use superior TSFs and the dynamic coupling between land use and its superior TSFs. Using this method, we found that the TSC of Qionglai City consists of 3, 7, and 14 first-, second-, and third-level space types, respectively. The key findings from this study are that land use superior TSFs show spatiotemporal heterogeneity in Qionglai, and coupling effects in spatial distribution were noted between land use types and their superior TSFs, as was temporal heterogeneity in the coupling degree and the structure of the TSFs corresponding to the land use types, which show obvious dynamics and non-stationarity of the functional structure. These findings confirm the necessity of considering the spatiotemporal heterogeneity of land use superior TSFs and the dynamic coupling between land use and its superior TSFs in TSC. This method of establishing a TSC system can be used to address a number of NTSP and management issues, and three examples are provided here: (a) zoning of urban, agricultural, and ecological space; (b) use planning of production, living and ecological space; (c) delimitation of urban development boundary, permanent basic farmland protection redline, and ecological protection redline

Spatially Explicit Reconstruction of Cropland Using the Random Forest: A Case Study of the Tuojiang River Basin, China from 1911 to 2010

A long-term, high-resolution cropland dataset plays an essential part in accurately and systematically understanding the mechanisms that drive cropland change and its effect on biogeochemical processes. However, current widely used spatially explicit cropland databases are developed according to a simple downscaling model and are associated with low resolution. By combining historical county-level cropland archive data with natural and anthropogenic variables, we developed a random forest model to spatialize the cropland distribution in the Tuojiang River Basin (TRB) during 1911–2010, using a resolution of 30 m. The reconstruction results showed that the cropland in the TRB increased from 1.13 × 104 km2 in 1911 to 1.81 × 104 km2. In comparison with satellite-based data for 1980, the reconstructed dataset approximated the remotely sensed cropland distribution. Our cropland map could capture cropland distribution details better than three widely used public cropland datasets, due to its high spatial heterogeneity and improved spatial resolution. The most critical factors driving the distribution of TRB cropland include nearby-cropland, elevation, and climatic conditions. This newly reconstructed cropland dataset can be used for long-term, accurate regional ecological simulation, and future policymaking. This novel reconstruction approach has the potential to be applied to other land use and cover types via its flexible framework and modifiable parameters

Copper accumulation and physiological markers of soybean (Glycine max) grown in agricultural soil amended with copper nanoparticles.

Copper-based nanoparticles (NPs) display a strong potential to replace copper salts (e.g., CuSO4) for application in agricultures as antimicrobial agents or nutritional amendments. Yet, their effects on crop quality are still not comprehensively understood. In this study, the Cu contents in soybeans grown in soils amended with Cu NPs and CuSO4 at 100-500 mg Cu/kg and the subsequent effects on the plant physiological markers were determined. The Cu NPs induced 29-89% at the flowering stage (on Day 40) and 100-165% at maturation stage (on Day 100) more Cu accumulation in soybeans than CuSO4. The presence of particle aggregates in the root cells with deformation upon the Cu NP exposure was observed by transmission electron microscopy. The Cu NPs at 100 and 200 mg/kg significantly improved the plant height and biomass, yet significantly inhibited at 500 mg/kg, compared to the control. In leaves chlorophyll-b was more sensitive than chlorophyll-a and carotenoids to the Cu NP effect. The Cu NPs significantly decreased the root nitrogen and phosphorus contents, while they significantly increased the leaf potassium content in comparison with control. Our results imply that cautious use of Cu NPs in agriculture is warranted due to relatively high uptake of Cu and altered nutrient quality in soybeans

Nitrogen addition may promote soil organic carbon storage and CO2 emission but reduce dissolved organic carbon in Zoige peatland

Summarization: With the increase of nitrogen (N) deposition, N input can affect soil C cycling since microbes may trigger a series of activities to balance the supply and demand of nutrients. However, as one of the largest C sinks on earth, the role of extra N addition in affecting peatland soil C and its potential mechanism remains unclear and debated. Therefore, this study chose the largest peatland in China (i.e., Zoige, mostly N-limited) to systematically explore the potential changes of soil C, microbes, and ecoenzymes caused by extra N input at the lab scale incubation. Three different types of soils were collected and incubated with different levels of NH4NO3 solution for 45 days. After incubation, N input generally increased soil organic C (SOC) but decreased dissolved organic carbon (DOC) in Zoige peatland soils. Moreover, CO2 and CH4 emissions were significantly increased after high N input (equal to 5 mg NH4NO3 g−1 dry soils). Through a series of analyses, it was observed that microbial communities and ecoenzyme activities mainly influenced the changes of different C components. Collectively, this study implied that the increasing N deposition might help C sequestration in N-limited peatland soils; simultaneously, the risk of increased CO2 and CH4 by N input in global warming should not be ignored.Presented on: Journal of Environmental Managemen