Rainstorms are one of the extreme rainfall events that cause serious disasters, such as urban flooding and mountain torrents. Traditional studies have used rain gauge observations to analyze rainstorm events, but relevant information is usually missing in gauge-sparse areas. Satellite-derived precipitation datasets serve as excellent supplements or substitutes for the gauge observations. By developing a grid-based rainstorm-identification tool, we used the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) time series product to reveal the spatial and temporal variabilities of rainstorms over China during 1998-2017. Significant patterns of both increasing and decreasing rainstorm occurrences were detected, with no spatially uniform trend being observed across the whole country. There was an increase in the area being affected by rainstorms during the 20-year period, with rainstorm centers shifting along the southwest-northeast direction. Rainstorm occurrence was found to be correlated with local total precipitation. By comparing rainstorm occurrence with climate variables such as the El Ni?o-Southern Oscillation and Pacific Decadal Oscillation, we also found that climate change was likely to be the primary reason for rainstorm occurrence in China. This study complements previous studies that used gauge observations by providing a better understanding of the spatiotemporal dynamics of China’s rainstorms.
Explicitly identifying the spatial distribution of ecological transition zones (ETZs) and simulating their response to climate scenarios is of significance in understanding the response and feedback of ecosystems to global climate change. In this study, a quantitative spatial identification method was developed to assess ETZ distribution in terms of the improved Holdridge life zone (iHLZ) model. Based on climate observations collected from 782 weather stations in China in the T0 (1981-2010) period, and the Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project (IPCC CMIP5) RCP2.6, RCP4.5, and RCP8.5 climate scenario data in the T1 (2011-2040), T2 (2041-2070), and T3 (2071-2100) periods, the spatial distribution of ETZs and their response to climate scenarios in China were simulated in the four periods of T0, T1, T2, and T3. Additionally, a spatial shift of mean center model was developed to quantitatively calculate the shift direction and distance of each ETZ type during the periods from T0 to T3. The simulated results revealed 41 ETZ types in China, accounting for 18% of the whole land area. Cold temperate grassland/humid forest and warm temperate arid forest (564,238.5 km 2), cold temperate humid forest and warm temperate arid/humid forest (566,549.75 km 2), and north humid/humid forest and cold temperate humid forest (525,750.25 km 2) were the main ETZ types, accounting for 35% of the total ETZ area in China. Between 2010 and 2100, the area of cold temperate desert shrub and warm temperate desert shrub/thorn steppe ETZs were projected to increase at a rate of 4% per decade, which represented an increase of 3604.2, 10063.1, and 17,242 km 2 per decade under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. The cold ETZ was projected to transform to the warm humid ETZ in the future. The average shift distance of the mean center in the north wet forest and cold temperate desert shrub/thorn grassland ETZs was generally larger than that of other ETZs, with the mean center moving to the northeast and the shift distance being more than 150 km during the periods from T0 to T3. In addition, with a gradual increase of temperature and precipitation, the ETZs in northern China displayed a shifting northward trend, while the area of ETZs in southern China decreased gradually, and their mean center moved to high-altitude areas. The effects of climate change on ETZs presented an increasing trend in China, especially in the Qinghai-Tibet Plateau.
Being a key ecological security barrier and production base for grassland animal husbandry in China, the balance between grassland forage supply and livestock-carrying pressure in North China directly affects grassland degradation and restoration, thereby impacting grassland ecosystem services. This paper analyzes the spatiotemporal variation in grassland vegetation coverage, forage supply, and the balance between grassland forage supply and livestock-carrying pressure from 2000 to 2015 in North China. We then discuss the spatial pattern of grassland ecological conservation under the impacts of grassland degradation and restoration, and livestock-carrying pressure. Over the last 16 years, the total grassland area in North China decreased by about 16,000 km 2, with vegetation coverage degraded by 6.7% of the grasslands but significantly restored by another 5.4% of grasslands. The provisioning of forage by natural grassland mainly increased over time, with an annual growth rate of approximately 0.3 kg/ha, but livestock-carrying pressure also increased continuously. The livestock-carrying pressure index without any supplementary feeding reached as high as 3.8. Apart from the potential livestock-carrying capacity in northeastern Inner Mongolia and the central Tibetan Plateau, most regions in North China are currently overloaded. Considering the actual supplementary feeding during the cold season, the livestock-carrying pressure index is about 3.1, with the livestock-carrying pressure mitigated in central and eastern Inner Mongolia. Assuming full supplementary feeding in the cold season, livestock-carrying pressure index will fall to 1.9, with the livestock-carrying pressure alleviated significantly in Inner Mongolia and on the Tibetan Plateau. Finally, we propose different conservation and development strategies to balance grassland ecological conservation and animal husbandry production in different regions of protected areas, pastoral areas, farming-pastoral ecotone, and farming areas, according to the grassland ecological protection patterns.
Alluviation and sedimentation of the Yellow River are important factors influencing the surface soil structure and organic carbon content in its lower reaches. Selecting Kaifeng and Zhoukou as typical cases of the Yellow River flooding area, the field survey, soil sample collection, laboratory experiment and Geographic Information System (GIS) spatial analysis methods were applied to study the spatial distribution characteristics and change mechanism of organic carbon components at different soil depths. The results revealed that the soil total organic carbon (TOC), active organic carbon (AOC) and nonactive organic carbon (NOC) contents ranged from 0.05-30.03 g/kg, 0.01-8.86 g/kg and 0.02-23.36 g/kg, respectively. The TOC, AOC and NOC contents in the surface soil layer were obviously higher than those in the lower soil layer, and the sequence of the content and change range within a single layer was TOC>NOC>AOC. Geostatistical analysis indicated that the TOC, AOC and NOC contents were commonly influenced by structural and random factors, and the influence magnitudes of these two factors were similar. The overall spatial trends of TOC, AOC and NOC remained relatively consistent from the 0-20 cm layer to the 20-100 cm layer, and the transition between high- and low-value areas was obvious, while the spatial variance was high. The AOC and NOC contents and spatial distribution better reflected TOC spatial variation and carbon accumulation areas. The distribution and depth of the sediment, agricultural land-use type, cropping system, fertilization method, tillage process and cultivation history were the main factors impacting the spatial variation in the soil organic carbon (SOC) components. Therefore, increasing the organic matter content, straw return, applying organic manure, adding exogenous particulate matter and conservation tillage are effective measures to improve the soil quality and attain sustainable agricultural development in the alluvial/sedimentary zone of the Yellow River.
In order to explore the water level variations of Caizi Lake under river-lake isolation, the monthly water level of the Chefuling station in Caizi Lake from 1989 to 2018 and the daily water level, rainfall and flow of local hydrological stations in 2018 were analyzed by using the Mann-Kendall trend test and wavelet analysis. Results showed that the difference of the average water level of Caizi Lake between the flood and dry seasons was 3.34 m, with a multi-year average water level of 10.42 m above sea level. The first and second main periods of the water level of Caizi Lake were 128 and 18 months, respectively, with 4 and 29 “up-down” cycles, respectively. From 2018, the next 3?4 years were likely to be the low water level period. The water level of Caizi Lake was significantly correlated with that of the Anqing hydrological station of the Yangtze River (r=0.824, P<0.01). In addition, the current hydrological staging of Caizi Lake was about 30 days behind than before the sluice was built. Under the dual influences of the river-lake isolation and the Yangtze-to-Huaihe Water Diversion Project (YHWD), the hydrological regime change of Caizi Lake and its eco-environmental effect needed long-term monitoring and research.
Scientifically assessing the economic impact of major public health emergencies, containing their negative effects, and enhancing the resilience of an economy are important national strategic needs. The new coronavirus disease (COVID-19) has, to date, been effectively contained in China, but the threat of imported cases and local risks still exist. The systematic identification of the virus’s path of influence and intensity is significant for economic recovery. This study is based on a refined multi-regional general equilibrium analysis model, which measures the economic and industrial impacts at different epidemic risk levels in China and simulates development trends and the degree of damage to industries and the economy under changes to supplies of production materials and product demand. The results show that, at the macroeconomic level, China’s GDP will decline about 0.4% to 0.8% compared to normal in 2020, with an average drop of about 2% in short-term consumption, an average drop in employment of about 0.7%, and an average increase in prices of about 0.9%. At the industry level, the epidemic will have the greatest short-term impact on consumer and labor- intensive industries. For example, the output value of the service industry will fall 6.3% compared to normal. Looking at the impact of the epidemic on the industrial system, the province most affected by the epidemic is Hubei, which is the only province in China in the level-1 risk category. As the disease spread outward from Hubei, there were clear differences in the main industries that were impacted in different regions. In addition, simulation results of recovery intensity of regional economies under the two epidemic response scenarios of resumption of work and production and active fiscal stimulus policies show that an increase in fiscal stimulus policies produces a 0.3% higher rate of gross regional product growth but it causes commodity prices to rise by about 1.8%. Measures to resume work and production offer a wider scope for industrial recovery.
Understanding the driving forces of regional air pollution and its mechanism has gained much attention in academic research, which can provide scientific policy-making basis for economy-environment sustainability in China. Being an important energy and industrial base, the North China Plain region has been experiencing severe air pollution. Therefore, understanding the relationship between industrialization and air quality in this region is of great importance for air quality improvement. In this study, the average annual concentrations of SO2, NO2 and PM10 in 47 sample cities at and above the prefecture level in the North China Plain region from 2007 to 2016 were used to illustrate the spatiotemporal characteristics of air pollution within this region. Furthermore, panel data model, panel vector autoregression model, and impulse response function were used to explore the correlation and driving mechanism between energy-intensive industries and regional air quality. The results show that：first, overall air quality improved in the study area between 2007 and 2016, with a significant greater fall in concentration of SO2 than that of NO2 and PM10; second, provincial border areas suffered from severe air pollution and showed an apparent spatial agglomeration trend of pollution; and third, the test results from different models all proved that energy-intensive industries such as the chemical, non-metallic mineral production, electric and thermal power production and supply industries, had a significant positive correlation with concentrations of air pollutants, and indicated an obvious short-term impulse response effect. It concludes that upgradation of industrial structure, especially that of energy-intensive industries, plays a very important role in the improvement of regional air quality, which is recommended to be put in top priority for authorities. Therefore, policies as increasing investments in technological innovation in energy-intensive industries, deepening cooperation in environmental governance between different provinces and cities, and strengthening supervision and entry restrictions are suggested.
Urban planning construction land standard is the technical specification for scientifically allocating various types of urban construction land, and it is the basis for drawing up and revising the overall urban planning scheme. Considering China’s current urban planning construction land standard, many problems exist, such as the gap in the land use control threshold, the lack of regional differences in the climate revision, and failing to consider the topographic factors. To resolve these problems, this study proposed a step-by-step process framework and quantitative calculation method for the establishment and revision of standards in accordance with the principle of Total-Structure control. By setting the conditions, a universal basic standard for construction land was established. Quantitative analysis was then conducted on the relationship between the basic standard and the selected key indicators, such as urban population size, sunshine spacing coefficient, the width of river valleys or inter-montane basins, and terrain slope, among others. Finally, revised standards were formed for climate conditions, topography, and geomorphologic conditions, which were matched with the basic standards. The key results are three-fold: (1) The per capita construction land standard of 95 m 2/person can be used as the total indicator of China’s urban planning basic standard, and the corresponding per capita single construction land comprises 32.50% of residential land, 7.42% of public management and public service land, 22.50% of industrial land, 17.50% of transportation facilities, 12.50% of green space, and 7.58% of other land-use types. The results of the revision of the urban population size indicate that the difference in population size has little effect on the total amount of per capita construction land. (2) The climate revision results of per capita residential land and per capita construction land in major cities reveal that the revised climate value varies greatly between north and south China. The revised climate values of the per capita area of construction land vary by latitude as follows: the value at 20°N is 93 m 2/person, the value at 30°N is 97 m 2/person, the value at 40°N is 103 m 2/person, and the value at 50°N is 115 m 2/person. The basic standard land value of 95 m 2/person is generally distributed across the Xiamen-Guilin-Kunming line. (3) The cities located in mountainous areas, hilly valleys, or inter-montane basins can reduce the allocation of community parks and comprehensive parks when the average width of an existing river valley or inter-montane basin is less than 2 km. When the average width of the valley or inter-montane basin is between 2 km to 4 km, the allocation of the comprehensive parks can be reduced. The revised results of per capita sloping construction land reveal that the terrain slope greatly affects the revised value of per capita construction land. Specifically, the revised value at 3° is 3.68% higher than the basic standard value, and the increase rates at 8°, 15°, and 25° are 11.25%, 26.49%, and 68.47%, respectively.
