Assessment of vegetation net primary productivity variation and influencing factors in the Beijing-Tianjin-Hebei region.

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m-2a-1. Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m-2a-1), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m-2a-1). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a-1 and 0.07 TgC·a-1, respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity.

Assessment of the impacts of land use changes on nonpoint source pollution inputs upstream of the Three Gorges Reservoir.

In recent years, land use upstream of the Three Gorges Reservoir (TGR) has changed significantly because of the TGR project. In this study, the Soil and Water Assessment Tool (SWAT) model was examined for its ability to assess relationships between land use changes and nonpoint pollutant indexes upstream of the TGR. Results indicated that the SWAT model, calibrated with the adjusted parameters, could successfully reproduce the nonpoint indexes at the water quality monitoring sites in the two rivers. The different land use change types were shown to be sensitive to nonpoint pollutants in the study area. The land use change type from upland to water was the strongest influence on changes in total nitrogen and total phosphorus. An empirical regression equation between nonpoint indexes and different land use change types was developed for the study area by partial least squares regression (PLSR) as follows: Y = b 0 + ∑ i=1 (m) b i X i. This regression equation was useful for evaluating the influence of land use change types on changes in nonpoint pollutants over a long time period. The results from this study may be useful for the TGR management and may help to reduce nonpoint pollutant loads into downstream water bodies.

Competitive and synergic evolution of the water-food-ecology system: A case study of the Beijing-Tianjin-Hebei region, China.

A vital approach to attaining sustainable development lies in the in-depth examination of both competition and synergy between these subsystems from a water-food-ecology (WFE) system perspective, while previous or existing studies have limitations in to quantitative characterize and evaluation the cooperative and competitive relationships between different systems. In this study, an evaluation indicator system is constructed from the two dimensions of resources and efficiency, and the WFE synergic development capacity (WFE-SDC) is proposed by integrating the order degree of the coupled system, enables a multidimensional and comprehensive quantitative assessment of the sustainable development of the WFE system. Then a synergic evolution model is constructed to explore the competitive and synergic evolution of the WFE system in the Beijing-Tianjin-Hebei region. The following key insights were obtained: (1) The WFE-SDC (range of 0-1) shows a fluctuating increase, indicating a shift from mild dysfunctional recession to intermediate synergic development (0.24 to 0.72). (2) Principal factors impeding WFE-SDC encompass diversion water, ecology water consumption, grain demand, reclaimed water consumption, and outbound water, both come from resource dimension, with a combined impediment degree of over 46 %, and the improvement of efficiency dimension may improve the WFE-SDC. (3) The water subsystem acts as a driving force for synergic development, fostering cooperation within the food and ecology subsystems, although they mainly operate in a competitive state. (4) Within the WFE system, Beijing, Tianjin, and Hebei exhibited mutual cooperation and significantly contributed to one another's development. Beijing has played a pivotal role in the progress of both Tianjin and Hebei. This study offers valuable insights for the formulation of policies and the application of technical approaches for the sustainable development of the WFE system in relevant regions.

Dry deposition effect of urban green spaces on ambient particulate matter pollution in China.

Particulate matter (PM) is a major source of urban air pollution that poses a serious threat to the environment and human health. This study quantified the dry deposition effect of PM2.5 and PM10 on vegetation using a mathematical model to overcome the limitations of traditional site-scale research. Additionally, multi-source satellite remote sensing products were combined to form a raster dataset to estimate the effect of dry deposition on PM2.5 and PM10 in China's urban green spaces from 2000 to 2020. The spatial and temporal changes in the long-term series were analyzed, and the influence of environmental factors on dry deposition was analyzed in combination with wavelet changes. The experimental results showed that: 1) from 2000 to 2020, the dry deposition effect of PM2.5 and PM10 on vegetation showed an initial increasing and then decreasing trend caused by the sudden drop in atmospheric pollutant particle concentration driven by local policies; 2) broad-leaved forests provided the main dry deposition effects in urban spaces, accounting for 89.22 %, indicating a need to increase the density of these forest types in urban development planning to improve air quality; and 3) PM2.5, PM10, and environmental impact factors have time-frequency scale coherences, and the coherence between PM2.5 reduction and these factors is more complex than that of PM10, with precipitation being the best variable to explain the change in PM2.5 and PM10. These findings are important for the prevention and control of urban air pollution, regional planning of green spaces, and sustainable development of cities.

Impact of land use changes on water quality in headwaters of the Three Gorges Reservoir.

The assessment of spatial and temporal variation of water quality influenced by land use is necessary to manage the environment sustainably in basin scales. Understanding the correlations between land use and different formats of nonpoint source nutrients pollutants is a priority in order to assess pollutants loading and predicting the impact on surface water quality. Forest, upland, paddy field, and pasture are the dominant land use in the study area, and their land use pattern status has direct connection with nonpoint source (NPS) pollutant loading. In this study, two land use scenarios (1995 and 2010) were used to evaluate the impact of land use changes on NPS pollutants loading in basins upstream of Three Gorges Reservoir (TGR), using a calibrated and validated version of the soil and water assessment tool (SWAT) model. The Pengxi River is one of the largest tributaries of the Yangtze River upstream of the TGR, and the study area included the basins of the Dong and Puli Rivers, two major tributaries of the Pengxi River. The results indicated that the calibrated SWAT model could successfully reproduce the loading of NPS pollutants in the basins of the Dong and Puli Rivers. During the 16-year study period, the land use changed markedly with obvious increase of water body and construction. Average distance was used to measure relative distribution patterns of land use types to basin outlets. Forest was mainly distributed in upstream areas whereas other land use types, in particular, water bodies and construction areas were mainly distributed in downstream areas. The precipitation showed a non-significant influence on NPS pollutants loading; to the contrary, interaction between precipitation and land use were significant sources of variation. The different types of land use change were sensitive to NPS pollutants as well as land use pattern. The influence of background value of soil nutrient on NPS pollutants loading was evaluated in upland and paddy field. It was found that total nitrogen (TN) and total phosphorous (TP) in upland were more sensitive to NPS pollutants loading than in paddy fields. The results of this study have implications for management of the TGR to reduce the loading of NPS pollutants into downstream water bodies.