LCZ method is more effective than traditional LUCC method in interpreting the relationship between urban landscape and atmospheric particles.

Landscape classification methods significantly impact the exploration of the mechanism of the relationship between landscapes and atmospheric particulate matter. This study compared the local climate zones (LCZs) and traditional land use/cover change (LUCC) landscape classification methods in explaining spatial differences in concentrations of atmospheric particulate matter (PM2.5 and PM10) and explored the mechanisms involved in how landscape elements affect atmospheric particulate matter. This was done by establishing a PM2.5 and PM10 land use regression (LUR) model of LCZ and LUCC landscapes under low, typical, and high particle concentration gradients in urban and suburban areas. The results show that under an LCZ classification system, the number of patches in the urban area of Shanghai was 548 times higher than that of a LUCC system. Moreover, LCZs were successfully established for LUR models in 12 scenarios, while only five models were established for LUCC, all of which were suburban models. The R2 of the LUR model based on the LCZ landscape and atmospheric particulate matter was mostly higher than that of the LUCC. For unnatural landscapes, the LUCC demonstrated that an urbanized environment positively affects the concentration of atmospheric particles. However, the LCZ analysis found that areas with high-density buildings have a positive effect on atmospheric particles, while most areas with low-density buildings significantly reduced the number of atmospheric particles present. Generally, compared with the traditional LUCC landscape classification method, LCZ integrates Shanghai's physical structure and classifies the urban landscape more accurately, which is closely related to the urban atmospheric particulate matter, especially in the urban area. Because the low-density building area has the same effect on the particulate matter as the natural landscape, the use of low-density buildings is recommended when planning new towns.

A data set of distributed global population and water withdrawal from 1960 to 2020.

Population and water withdrawal data sets are currently faced with difficulties in collecting, processing and verifying multi-source time series, and the spatial distribution characteristics of long series are also relatively lacking. Time series is the basic guarantee for the accuracy of data sets, and the production of long series spatial distribution is a realistic requirement to expand the application scope of data sets. Through the time-consuming and laborious basic processing work, this research focuses on the population and water intake time series, and interpolates and extends them to specific land uses to ensure the accuracy of the time series and the demand of spatially distributed data sets. This research provides a set of population density and water intensity products from 1960 to 2020 distributed to the administrative units or the corresponding regions. The data set fills the gaps in the multi-year data set for the accuracy of population density and the intensity of water withdrawal.

Effects of revetments on soil ecosystems in the urban river-riparian interface.

By altering material and energy exchange between river and riparian, the city revetments have an unknown impact on the service function of river-riparian interface (RRI) ecosystems. This study analyzes the differences in natural, permeable (PR), and impervious revetment (IR). We found that the water-filled porosity of revetment increased from 20% to 100%, which coincided with an increase in soil potassium, air-filled porosity, the surface soil of moisture and organic matter (SOM), and a decrease in soil nitrogen, phosphorus nutrients, and in the middle and deep soil SOM. The changes affected the abundance of dominant bacterial and fungi genera. Compared with the PR, surface soil moisture, pH, and underground biomass were lower in IR surface soils, while surface soil SOM and middle soil moisture were higher. This research provides a development direction and theoretical basis for future urban planning and environmental governance.

Freeze-thaw cycle frequency affects root growth of alpine meadow through changing soil moisture and nutrients.

Alpine meadows grow in alpine regions and play an important role in the production and life of alpine regions. As a unique feature of alpine regions, freeze-thaw cycles (FTCs) affect the growth of alpine meadows. However, with climate change, the change in the freeze-thaw cycle frequency (FTCF) has become obvious. These changes affect the content and distribution of soil moisture and nutrients, as well as the growth of roots in the alpine meadow. Therefore, based on the analysis of FTCF in the Nagqu River Basin, the characteristics of soil moisture, nutrients, and alpine meadow roots are analyzed, thus revealing the influence mechanism of FTCF on the root growth of alpine meadows. The results highlight three major findings. (1) Compared with the low-frequency mode (LFM), the moisture at 0-20, 20-40, and 40-60 cm in the high-frequency mode (HFM) has decreased by 30.74%, 52.89%, and 47.52%, respectively. Additionally, in HFM the contents of soil hydrolysable nitrogen (HN), available K (AK), and microbial biomass carbon (MBC) at the same depth are lower than those in LFM. (2) The original distribution of soil moisture at 0-60 cm has gradually increased from the surface to the bottom. However, with the increase in FTCF, the distribution of the soil moisture now means that the soil moisture at the surface (0-20 cm) and the deeper layers (40-60 cm) is higher than that in the middle (20-40 cm). (3) With the increase in FTCF, the growth mode of alpine meadow roots has changed from vertical extension to horizontal divergence; the distribution range of roots has changed from 0-40 cm to 0-20 cm; the length, surface area, and volume of 0-0.5 mm roots have increased by 20.95 cm, 1.90 cm2, and 0.014 cm3; and the corresponding specific gravity has increased by 9.09%, 13.50%, and 12.14%, respectively. This study provides a theoretical basis for predicting the growth mode of alpine meadow roots in the Nagqu River Basin under the influence of climate change and provides guidance for protecting the ecology of alpine regions and mitigating and solving global climate change.

Effect of Climate Change on CO2 Flux in Temperate Grassland, Subtropical Artificial Coniferous Forest and Tropical Rain Forest Ecosystems.

The interactions between CO2 flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004-2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003-2010), and the tropical rain forest (TRF) of Xishuangbanna (2003-2010). The main factors of climate change affecting ecosystem CO2 flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO2 flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO2 flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.

A data set of global river networks and corresponding water resources zones divisions.

As basic data, the river networks and water resources zones (WRZ) are critical for planning, utilization, development, conservation and management of water resources. Currently, the river network and WRZ of world are most obtained based on digital elevation model data automatically, which are not accuracy enough, especially in plains. In addition, the WRZ code is inconsistent with the river network, hindering the efficiency of data in hydrology and water resources research. Based on the global 90-meter DEM data combined with a large number of auxiliary data, this paper proposed a series of methods for generating river network and water resources zones, and then obtained high-precision global river network and corresponding WRZs at level 1 to 4. The dataset provides generated rivers with high prevision and more accurate position, reasonable basin boundaries especially in inland and plain area, also the first set of global WRZ at level 1 to 4 with unified code. It can provide an important basis and support for reasonable use of water resources and sustainable social development in the world.