Integrating GNSS and GRACE Observations to Investigate Water Storage Variations Across Different Climatic Regions of China

Predicting daily solar radiation using a novel hybrid long short-term memory network across four climate regions of China

Discussion of the Adaption of between Blinds Glass for Residential Buildings in Different Climate Regions of China Based on Energy Consumption Analysis

Analysis and optimization of external venetian blind shading for nearly zero-energy buildings in different climate regions of China

Variations of surface soil δ13Corg in the different climatic regions of China and paleoclimatic implication

Historical peak situation of building carbon emissions in different climate regions in China: Causes of differences and peak challenges

Improving the sustainability of milk production across different climate regions in China

Energy-saving analysis of a case data center with a pump-driven loop heat pipe system in different climate regions in China

Contributions of energy-saving technologies to building energy saving in different climatic regions of China

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 32:219-227 (2006) - doi:10.3354/cr032219 Influence of climate on winter wheat productivity in different climate regions of China, 1961–2000 Yanling Song1,2,*, Deliang Chen3,4, Wenjie Dong3 1Chinese Academy of Sciences Key Laboratory of Regional Climate–Environment Research for Temperate East Asia, START Regional Center for Temperate East Asia, Institute of Atmospheric Physics, Qijiahuozi Road, Chaoyang, Beijing 100029, China 2Graduate School of the Chinese Academy of Sciences, 19 Yuquan Road, Shijingshan, Beijing 100049, China 3National Climate Center, China Meteorological Administration, 46 Zhongquancun Road, Beijing 100081, China 4Earth Sciences Centre, University of Gothenburg, Box 460, 405 30 Göteborg, Sweden *Email: anna_song74@yahoo.com.cn ABSTRACT: The World Food Studies crop model (WOFOST) was tuned and validated with observed meteorological data as well as winter wheat growth and yield data for 50 stations in 12 provinces in China from 1998 to 2003. The results show that most of the simulated growth dates and yields lie within ±15% range of the observed data, showing that the genetic parameters determined are reasonable in most winter wheat regions of China. Overall, the results demonstrate that the WOFOST model predicts potential winter wheat yields (assuming there are no limits imposed by water availability) and growth reasonably well under current climatic conditions. By assuming winter wheat varieties and agricultural practices stay constant, the parameterization obtained by the tuning was then used to model the impacts of climate on winter wheat growth for the 50 stations using long-term weather data from 1961 to 2000. Over this period, the simulated potential yield of winter wheat in northern China increased by 2.3%, while decreasing by 1.6% in southern China. In northern China, the accumulated negative temperatures during winter increased by 29.3°C decade–1, which is most likely the main reason for the increased potential yield of winter wheat. In southern China, one possible reason for the decreased potential yield is a shortened growth interval for winter wheat caused by the increasing mean temperatures. KEY WORDS: Crop growth model · WOFOST · Climate change · Winter wheat · China Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 32, No. 3. Online publication date: October 26, 2006 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2006 Inter-Research.

Evaluation and development of empirical models for estimating daily and monthly mean daily diffuse horizontal solar radiation for different climatic regions of China

Numerical evaluation on energy saving potential of the photovoltaic fresh air preheating system in different climate regions of China

Global warming has an impact on building performance, and it is very important to explore the optimization of building performance under future climate change conditions. The study generates 2050s typical meteorological year (TMY) data of different cities (Harbin, Beijing, Shanghai, Shenzhen) representing the future climate. Taking energy consumption, thermal comfort, and initial investment cost as the objective function, the Back Propagation (BP) neural network and non-dominated sorting genetic algorithm (NSGA-Ⅱ) were used to optimize the key parameters of the building envelope of representative cities in different climate regions of China and to obtain the Pareto curve. The final solution is obtained by the weighted sum method (WSM). The results show that, except for the type of windows, the optimal configuration of the building envelope in each city is different. Compared with the results of reference buildings, the final results of each city reduces energy consumption by 14.5~24.0 % and improves thermal comfort by 23.8~34 % when the initial investment cost increases by 27.0~35.3 %. The method proposed in this paper has reference significance for the optimization of building envelope in different climatic regions of China under the future climate.

Annual energetic evaluation of multi-stage dedicated mechanical subcooling carbon dioxide supermarket refrigeration system in different climate regions of China using genetic algorithm

Determining the optimum insulation thicknesses of external envelopes for livestock buildings are one of the most effective metrics to decrease energy requirements. This study was carried out to determine the optimum insulation thicknesses for livestock buildings in different climate zones, to examine the effects of insulation thickness and material (foam glass, mineral wool, expanded polystyrene, foamed polyurethane, foamed polyvinyl chloride, and expanded polyethylene) on life cycle total cost, life cycle savings, and payback period. The finishing pig houses and laying hen buildings with sandwich wall structures (color steel laminboard) in five typical cities were studied using the degree-days method with economic models. Optimal insulation thicknesses ranged from 0.05 m to 0.25 m and 0.02 m to 0.24 m in finishing pig houses and poultry buildings, respectively; the life cycle total costs ranged from 16.49 to 37.98 $/m2 and 13.37 to 36.84 $/m2; the life cycle savings ranged from 29.13 to 220.60 $/m2 and 0 to 202.13 $/m2; and the payback period ranged from 1.11 to 5.81 years and 1.19 to 20.76 years, respectively. Foamed polyurethane provided the highest life cycle savings, while foam glass had the lowest. In this research, the insulation thicknesses for the sandwich structure livestock buildings external envelopes are optimized, and the energy saving can be obtained by using proper insulation thickness in different regions. Furthermore, it can increase the knowledge about energy consumption in the livestock buildings and the results can be also a useful tool for farmers. Keywords: livestock building, insulation material, optimum insulation thicknesses, degree-days, life cycle total cost, life cycle saving, payback period DOI: 10.25165/j.ijabe.20201301.5280 Citation: Wang Y, Li B M, Zheng W C. Optimum insulation thickness for the sandwich structure livestock buildings external envelopes in different climate regions of China. Int J Agric & Biol Eng, 2020; 13(1): 29–41.

Distributions of branched glycerol dialkyl glycerol tetraethers (brGDGTs) from soil bacteria have been recently used for reconstructions of past soil pH and air temperature history. Here, we report the brGDGTs distribution patterns from different climate regions of China, using 42 novel brGDGT data from sub-tropical Chinese soils, compiled alongside previously-published data encompassing different environmental conditions across China. These patterns show high abundance of Ia fraction in soils from humid areas, and high abundance of IIa′ and IIIa′ fractions corresponds to semi-humid or semi-arid conditions, implying a possible relationship with precipitation. The abundance of IIa fraction appears negatively correlated with air temperature. Statistically, the soil pH and temperature factors represent 62% and 30% variations of the total variance respectively. For soils from humid and semi-humid regions, strong correlations between cyclization of branched tetraethers (CBT′) index and soil pH (R2 = 0.89) and between methylation of branched tetraethers (MBT′5ME) index and mean annual temperature (MAT)(R2 = 0.82) exist. When soils from semi-arid regions are included, the correlations become slightly stronger with pH and significantly weaker with MAT. Our study confirms the usefulness of soil brGDGTs distributions for Quaternary palaeo-climate reconstructions.