Spatiotemporal variations, influence factors, and simulation of global cooling degree days.

The cooling degree days (CDDs) can indicate the hot climatic impacts on energy consumption and thermal environment comfort effectively. Nevertheless, seldom studies focused on the spatiotemporal characteristics, influence factors, and simulation of global CDDs. This study analyzed the spatial-temporal characteristics of global CDDs from 1970 to 2018 and in the future, explored five determinants, and simulated CDDs and their interannual changing rates. The results showed that the global CDDs were generally higher at lower latitudes and altitudes. Many places experienced significant positive changes of CDDs (p < 0.05), and the rates became larger at lower latitudes and attitudes. In the future, most CDDs had the sustainability trends. Besides, significant negative partial correlations existed between not only CDDs but also their variation rates with latitude, altitude, and average enhanced vegetation index in the summer, while positive with the annual PM2.5, distance to large waterbodies (p = 0.000). Moreover, the values and variation rates of CDDs can be deduced using the generalized regression neural network method. The root-mean-square errors were 231.73 °C * days and 1.71 °C * days * year-1, respectively. These conclusions were helpful for the energy-saving for cooling with the climate change and optimization of thermal environment.

Vegetation Dynamics in Response to Climate Change and Human Activities in a Typical Alpine Region in the Tibetan Plateau.

Understanding past and future vegetation dynamics is important for assessing the effectiveness of ecological engineering, designing policies for adaptive ecological management, and improving the ecological environment. Here, inter-annual changes in vegetation dynamics during 2000-2020, contributions of climate change (CC) and human activities (HA) to vegetation dynamics, and sustainability of vegetation dynamics in the future were determined in Gannan Prefecture (a typical alpine region in the Tibetan Plateau), China. MODIS-based normalized difference vegetation index (NDVI), air temperature, precipitation, and land cover data were used, and trend analysis, multiple regression residuals analysis, and Hurst exponent analysis were employed. NDVI increased at a rate of 2.4 × 10-3∙a-1 during the growing season, and vegetation improved in most parts of the study area and some sporadically degraded areas also existed. The increasing rate was the highest in the Grain to Green Project (GTGP) areas. The vegetation in the southern and northern regions was mainly affected by CC and HA, respectively, with CC and HA contributions to vegetation change being 52.32% and 47.68%, respectively. The GTGP area (59.89%) was most evidently affected by HA. Moreover, a Hurst exponent analysis indicated that, in the future, the vegetation in Gannan Prefecture would continuously improve. The study can assist in formulating ecological protection and restoration projects and ensuring sustainable development.

Spatial-Temporal Changes and Associated Determinants of Global Heating Degree Days.

The heating degree days (HDDs) could indicate the climate impact on energy consumption and thermal environment conditions effectively during the winter season. Nevertheless, studies on the spatial-temporal changes in global HDDs and their determinants are scarce. This study used multi-source data and several methods to explore the rules of the spatial distribution of global HDDs and their interannual changes over the past 49 years and some critical determinants. The results show that global HDDs generally became larger in regions with higher latitudes and altitudes. Most global change rates of HDDs were negative (p < 0.10) and decreased to a greater extent in areas with higher latitudes. Most global HDDs showed sustainability trends in the future. Both the HDDs and their change rates were significantly partially correlated with latitude, altitude, mean albedo, and EVI during winter, annual mean PM2.5 concentration, and nighttime light intensity (p = 0.000). The HDDs and their change rates could be simulated well by the machine learning method. Their RMSEs were 564.08 °C * days and 3.59 °C * days * year-1, respectively. Our findings could support the scientific response to climate warming, the construction of living environments, sustainable development, etc.

A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling.

The world is faced with significant climate change, rapid urbanization, massive energy consumption, and tremendous pressure to reduce greenhouse gases. Building heating and cooling is one primary source of energy consumption and anthropogenic carbon dioxide emissions. First, this review presents previous studies that estimate the specific amount of climate change impact on building heating and cooling energy consumption, using the statistical method, physical model method, comprehensive assessment model method, and the combination method of statistical and physical model methods. Then, because the heating and cooling degree days indices can simply and reliably indicate the effects of climate on building heating and cooling energy consumption, previous studies were reviewed from the aspects of heating and cooling degree days indices, regional spatial-temporal variations in degree days and related indices, influencing factors of the spatial distributions of degree days, and the impacts of urbanization on degree days. Finally, several potential key issues or research directions were presented according to the research gaps or fields that need to be studied further in the future, such as developing methods to simply and accurately estimate the specified amounts of climate change impact on building cooling and heating energy consumption; using more effective methods to analyze the daytime, nighttime, and all-day spatial-temporal changes in different seasons in the past and future under various environment contexts by considering not only the air temperature but also the relative humidity, solar radiation, population, etc., and further exploring the corresponding more kinds of driving forces, including the various remotely sensed indices, albedo, nighttime light intensity, etc.; estimating the daytime, nighttime, and all-day impacts of urbanization on heating degree days (HDDs), cooling degree days (CDDs), and their sum (HDDs + CDDs) for vast cities in different environmental contexts at the station site, city, regional and global scales; producing and sharing of the related datasets; and analyzing the subsequent effects induced by climate change on the energy consumption for building heating and cooling, etc.

An inverted U-shaped curve relating farmland vulnerability to biological disasters: Implications for sustainable intensification in China.

Sustainable farmland intensification is necessary in order to harmonize relationships between food security, socioeconomic development, and ecological civilization. However, the degradation of farmland sustainability because of biological disasters represents a major challenge if we are to achieve this intensification. Our understanding of farmland vulnerability to biological disasters (FVBD) remains relatively rudimentary and subjective, limiting its effectiveness as a tool for farmland sustainability analysis. Limited research has also been carried out on FVBD changes taking into account human decisions on farmland use. The aim of this study is to achieve a novel understanding of FVBD change and its implications for sustainable intensification using evidence from Chinese farmland use. A theoretical framework based on an inverted U-shaped curve that depicts FVBD as well as an assessment framework for FVBD were established using induced substitution of agricultural production. Across China and considering 15 provincial districts with scarce farmland, the relationship between FVBD and socio-economic development was identified as consistent with an inverted U-shaped curve at both national and provincial levels. FVBD values in 2016 across Southern China, on the Huang-Huai-Hai Plain, and on the middle-lower Yangtze Plain were 45.44, 40.58, and 37.22, respectively. These values also decreased in provinces on the middle-lower Yangtze Plain between 1995 and 2016, but increased markedly across provinces in Southern China and on the Huang-Huai-Hai Plain. Contributions to FVBD changes during stages of growth and decline were also analyzed between 1995 and 2016. An inverted U-shaped curve was effective in investigating the responses of farmland sustainability to a range of alternative future socioeconomic development pathways. Thus, in the Chinese settings, a typical country with scarce farmland, policies on FVBD control are essential if we are to promote sustainable farmland intensification. The findings of this work are important and present us with a new way to understand FVBD from a human perspective.

Land Cover Change Intensifies Actual and Potential Radiative Forcing through CO2 in South and Southeast Asia from 1992 to 2015.

Land cover change (LCC) and its impact on CO2 sequestration and radiative forcing (RF) could dramatically affect climate change, but there has been little effort to address this issue in South and Southeast Asia over a long period of time using actual land cover information. In this study, annual land cover data from 1992 to 2015 were used to assess the CO2 flux and corresponding RF due to LCC in South and Southeast Asia. The results showed that 553.2 × 103 km2 of the region experienced LCC during this period, mostly due to land reclamation, urban expansion, and deforestation. These LCC caused a marked net decrease in net ecosystem productivity (NEP) as a composite of the various land cover categories during the whole study period, especially since 2001. The CO2 sequestration was 2160 TgCO2 during the early 1990s however cumulative sequestration decreased by 414.95 TgCO2 by 2015. Correspondingly, the cooling effect of NEP, i.e. the total actual RF, was -0.366 W m-2 in South and Southeast Asia between 1992 and 2015. However, the potential RF of the cumulatively reduced NEP due to LCC relative to the 1990s resulted in a warming effect of 2.33 × 10-3 W m-2 in 2015. Our study provides an applicable framework to accurately assess the potential effect of large-scale LCC on climate.

Continuous monitoring of lake dynamics on the Mongolian Plateau using all available Landsat imagery and Google Earth Engine.

Lakes are important water resources on the Mongolian Plateau (MP) for human's livelihood and production as well as maintaining ecosystem services. Previous studies, based on the Landsat-based analyses at epoch scale and visual interpretation approach, have reported a significant loss in the lake areas and numbers, especially from the late 1990s to 2010. Given the remarkable inter- and intra-annual variations of lakes in the arid and semi-arid region, a comprehensive picture of annual lake dynamics is needed. Here we took advantages of the power of all the available Landsat images and the cloud computing platform Google Earth Engine (GEE) to map water body for each scene, and then extracted lakes by post-processing including raster-to-vector conversion and separation of lakes and rivers. Continuous dynamics of the lakes over 1 km2 was monitored annually on the MP from 1991 to 2017. We found a significant shrinkage in the lake areas and numbers of the MP from 1991 to 2009, then the decreasing lakes on the MP have recovered since circa 2009. Specifically, Inner Mongolia of China experienced more dramatic lake variations than Mongolia. A few administrative regions with huge lakes, including Hulunbuir and Xilin Gol in Inner Mongolia and Ubsa in Mongolia, dominated the lake area variations in the study area, suggesting that the prior treatments on these major lakes would be critical for water management on the MP. The varied drivers of lake variations in different regions showed the complexity of factors impacting lakes. While both natural and anthropogenic factors significantly affected lake dynamics before 2009, precipitation played increasingly important role for the recovery of lakes on the MP after 2009.

[Assessment on the changing conditions of ecosystems in key ecological function zones in China].

In this paper, the dynamics of ecosystem macrostructure, qualities and core services during 2000 and 2010 were analyzed for the key ecological function zones of China, which were classified into four types of water conservation, soil conservation, wind prevention and sand fixation, and biodiversity maintenance. In the water conservation ecological function zones, the areas of forest and grassland ecosystems were decreased whereas water bodies and wetland were increased in the past 11 years, and the water conservation volume of forest, grassland and wetland ecosystems increased by 2.9%. This region needs to reverse the decreasing trends of forest and grassland ecosystems. In the soil conservation ecological function zones, the area of farmland ecosystem was decreased, and the areas of forest, grassland, water bodies and wetland ecosystems were increased. The total amount of the soil erosion was reduced by 28.2%, however, the soil conservation amount of ecosystems increased by 38.1%. In the wind prevention and sand fixation ecological function zones, the areas of grassland, water bodies and wetland ecosystems were decreased, but forest and farmland ecosystems were increased. The unit amount of the soil. wind erosion was reduced and the sand fixation amount of ecosystems increased lightly. In this kind of region that is located in arid and semiarid areas, ecological conservation needs to reduce farmland area and give priority to the protection of the original ecological system. In the biodiversity maintenance ecological function zones, the areas of grassland and desert ecosystems were decreased and other types were increased. The human disturbances showed a weakly upward trend and needs to be reduced. The key ecological function zones should be aimed at the core services and the protecting objects, to assess quantitatively on the effectiveness of ecosystem conservation and improvement.