Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

Surface air temperature change in the Wuyi Mountains,southeast China

Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.

Effects of temperature, particle size, and air humidity on sensibility of typical high-energetic explosives

The production and utilization of high-energetic explosives often pose a range of safety hazards,with sensitivity being a key factor in evaluating these risks.To investigate how temperature,particle size,and air humidity affect the responsiveness of commonly used high-energetic explosives,a series of BAM(Bundesanstalt für Materialforschung und-prüfung)impact and friction sensitivity tests were carried out to determine the critical impact energy and critical load pressure of four representative high-energetic explosives(RDX,HMX,PETN and CL-20)under different temperatures,particle sizes,and air humidity conditions.The experimental findings facilitated an examination of temperature and particle size affecting the sensitivity of high-energetic explosives,along with an assessment of the influence of air humidity on sensitivity testing.The results clearly indicate that high-energetic explosives display a substantial decline in critical reaction energy when subjected to micrometre-sized particles and an air humidity level of 45%at a temperature of 90℃.Furthermore,it was noted that the critical reaction energy of high-energetic explosives diminishes with an increase in temperature within 25℃−90℃.In the same vein,as the particle sizes of high-energetic explosives increase,so does the critical reaction energy for micrometre-sized particles.High air humidity significantly affects the sensitivity testing of high-energetic explosives,emphasizing the importance of refraining from conducting sensitivity tests in such conditions.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

Spatial Variation in CO_(2) Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

The increasing concentration of atmospheric CO_(2) since the Industrial Revolution has affected surface air temperature.However,the impact of the spatial distribution of atmospheric CO_(2) concentration on surface air temperature biases remains highly unclear.By incorporating the spatial distribution of satellite-derived atmospheric CO_(2) concentration in the Beijing Normal University Earth System Model,this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere(NH) under historical conditions from 1976-2005.In comparison with the increase in surface temperature simulated using a uniform distribution of CO_(2),simulation with a nonuniform distribution of CO_(2)produced better agreement with the Climatic Research Unit(CRU) data in the NH under the historical condition relative to the baseline over the period 1901-30.Hemispheric June-July-August(JJA) surface air temperature increased by 1.28℃ ±0.29℃ in simulations with a uniform distribution of CO_(2),by 1.00℃±0.24℃ in simulations with a non-uniform distribution of CO_(2),and by 0.24℃ in the CRU data.The decrease in downward shortwave radiation in the non-uniform CO_(2) simulation was primarily attributable to reduced warming in Eurasia,combined with feedbacks resulting from increased leaf area index(LAI) and latent heat fluxes.These effects were more pronounced in the non-uniform CO_(2)simulation compared to the uniform CO_(2) simulation.Results indicate that consideration of the spatial distribution of CO_(2)concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models.

Influence of the Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation on Antarctic surface air temperature during 1900 to 2015

The importance of the Atlantic Multidecadal Oscillation(AMO)and Interdecadal Pacific Oscillation(IPO)in influencing zonally asymmetric changes in Antarctic surface air temperature(SAT)has been established.However,previous studies have primarily concentrated on examining the combined impact of the contrasting phases of the AMO and IPO,which have been dominant since the advent of satellite observations in 1979.This study utilizes long-term reanalysis data to investigate the impact of four combinations of+AMO+IPO,–AMO–IPO,+AMO–IPO,and–AMO+IPO on Antarctic SAT over the past 115 years.The+AMO phase is characterized by a spatial mean temperature amplitude of up to 0.5℃over the North Atlantic Ocean,accompanied by positive sea surface temperature(SST)anomalies in the tropical eastern Pacific and negative SST anomalies in the extratropical-mid-latitude western Pacific,which are indicative of the+IPO phase.The Antarctic SAT exhibits contrasting spatial patterns during the+AMO+IPO and+AMO–IPO periods.However,during the–AMO+IPO period,apart from the Antarctic Peninsula and the vicinity of the Weddell Sea,the entire Antarctic region experiences a warming trend.The most pronounced signal in the SAT anomalies is observed during the austral autumn,whereas the combination of–AMO and–IPO exhibits the smallest magnitude across all the combinations.The wavetrain excited by the SST anomalies associated with the AMO and IPO induces upper-level and surface atmospheric circulation anomalies,which alter the SAT anomalies.Furthermore,downward longwave radiation anomalies related to anomalous cloud cover play a crucial role.In the future,if the phases of AMO and IPO were to reverse(AMO transitioning to a negative phase and IPO transitioning to a positive phase),Antarctica could potentially face more pronounced warming and accelerated melting compared to the current observations.

Response of Rice Cultivars to Elevated Air Temperature and Soil Amendments: Implications towards Climate Change Adaptations and Mitigating Global Warming Potentials

Global mean surface air temperature is expected to increase 1.1˚C - 6.4˚C by the end of 21st century which may affect rice productivity and methane emissions in the future climate. This experiment was conducted to investigate the response of rice cultivars to elevated air temperature (+1.5˚C higher than ambient) and soil amendments in regards to rice yield, yield scaled methane emissions and global warming potentials. The experimental findings revealed that replacement of inorganic fertilizers (20% - 40% of recommended NPKS) with Vermicompost, Azolla biofertilizer, enriched sugarcane pressmud, rice husk biochar and silicate fertilization increased rice yield 13.0% - 23.0%, and 11.0% - 19.0% during wet aman and dry boro season, respectively. However, seasonal cumulative CH4 fluxes were decreased by 9.0% - 25.0% and 5.0% - 19.0% during rainfed wet aman and irrigated dry boro rice cultivation, respectively with selected soil amendments. The maximum reduction in seasonal cumulative CH4 flux (19.0% - 25.0%) was recorded with silicate fertilization and azolla biofertilizer amendments (9.0% - 13.0%), whereas maximum grain yield increment 10.0 % - 14.0% was found with Vermicompost and Sugarcane pressmud amendments compared to chemical fertilization (100% NPKS) treated soils at ambient air temperature. However, rice grain yield decreased drastically 43.0% - 50.0% at elevated air temperature (3˚C higher than ambient air temperature), eventhough accelerated the total cumulative CH4 flux as well as GWPs in all treatments. Maximum seasonal mean GWPs were calculated at 391.0 kg CO2 eq·ha−1 in rice husk biochar followed by sugarcane pressmud (mean GWP 387.0 kg CO2 eq·ha−1), while least GWPs were calculated at 285 - 305 kg CO2 eq·ha−1 with silicate fertilizer and Azolla biofertilizer amendments. Rice cultivar BRRI dhan 87 revealed comparatively higher seasonal cumulative CH4 fluxes, yield scaled CH4 flux and GWPs than BRRI dhan 71 during wet aman rice growing season;while BRRI dhan 89 showed higher cumulative CH4 flux and GWPs than BINA dhan 10 during irrigated boro rice cultivation. Conclusively, inorganic fertilizers may be partially (20% - 40% of the recommended NPKS) replaced with Vermicompost, azolla biofertilizer, silicate fertilizer and enriched sugarcane pressmud compost for sustainable rice production and decreasing GWPs under elevated air temperature condition.

Urban Surroundings Influence on Air Temperature in a Small Urban Area of Curitiba-Brazil

The formation of urban climates constitutes a distinctive system intrinsically linked to the urban environment. This study aims to delve into the impact of the urban environment on climatic variables. The Urban Weather Generator (UWG) algorithm was employed to generate climatic data, facilitating the creation of an epw climate file that corresponds to the urban characteristics surrounding the Centro Politécnico campus at the Federal University of Paraná (UFPR). Comprehensive analyses encompassing land use, occupancy patterns, albedo, surface absorption, anthropogenic heat, and architectural attributes were conducted. A comparative assessment between the UWG-derived air temperature values and meteorological station data revealed that the UWG effectively characterizes the air temperature patterns around the UFPR campus. The anticipated air temperature values consistently surpass the original dataset (SWERA), which was utilized as input, primarily during the hours from 3 p.m. to 7 a.m., showcasing the unmistakable urban heat island phenomenon.

Analysis of Extreme Temperature Variability in Rwanda

The temperature is one of the most important factors in weather and climate forecasting.Studying its behaviour is crucial to understanding climate variability,which could vary spatially and temporally at local,regional,and global scales.Several recent studies on air temperature findings show that the Earth’s near surface air temperature increased between 0.6℃ and 0.8℃ throughout the twentieth century.Using temperature records from ten meteorological stations,this study examined climate variability in Rwanda from the 1930s to 2014.The air temperature data were collected from Meteo Rwanda.Before making the analysis,the authors used software,such as Excel 2007 and INSTAT to control the quality of the raw data.The analysis of maxima and minima indicated that the trends of maximum air temperature were positive and significant at height meteorological stations,whereas the trends for minimum air temperature were found to be at 10 meteorological stations.For all parameters analysed,Kigali Airport meteorological station indicated the higher significance of the trends.The majority of meteorological stations showed an increase in both hot days and nights,confirming Rwanda’s warming over time.The analysis of average seasonal air temperature showed almost similar trends even though not all were significant.This similarity in trends could be attributed to the fact that Rwanda’s short and long dry seasons coincide with rainy seasons.

Decadal prediction skill for Eurasian surface air temperature in CMIP6 models

评估CMIP6年代际预测试验对季节平均SAT的预测技巧的结果表明:模式不能有效预测冬季和秋季SAT的年代际变率.IPSL-CM6A-LR和多模式集合平均对于春季SAT展现了预测技巧,其中对于变率的预测技巧好于振幅的结果.基于蒙古和我国华北地区的显著预测技巧,模式对于夏季SAT表现出最佳的预测水平.与外部强迫相比,模式对于SAT的预测技巧可能来自初始化.模式中的一个明显系统性误差值得注意,即模式中冬季SAT的变率可以持续到其他季节,而在观测中其他季节的SAT变化与冬季SAT相对独立.

Analysis of Temperature Trends and Variations in the Arabian Peninsula’s Upper Atmosphere

In this study, the trends of upper-air temperatures are analysed by utilising radiosonde observations for the barometric levels at 700, 500, 300, 200, 150, 100 and 50 hPa from five meteorological stations within the Arabian Peninsula from January 1986 to August 2015. The mean monthly variations of the temperatures at these levels are characterised and established. The magnitudes of the annual trends of the mean temperatures for each site for the selected barometric levels are studied and statistically tested using Mann-Kendall rank statistics at different significance levels. The temperature trends at different pressure levels show that the upper troposphere and lower stratosphere are warming, while the middle troposphere is cooling which is consistent with the findings of other studies. The variations in upper air temperature observed in this study can be attributed to a range of factors, including increasing greenhouse gas concentrations, changes in atmospheric circulation patterns, variations in solar activity, aerosols and volcanic eruptions, and land use and land cover change.

Estimating Monthly Surface Air Temperature Using MODIS LST Data and an Artificial Neural Network in the Loess Plateau, China

Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather station networks is insufficient,especially in sparsely populated regions,greatly limiting the accuracy of estimates of spatially distributed Ta.Due to their continuous spatial coverage,remotely sensed land surface temperature(LST)data provide the possibility of exploring spatial estimates of Ta.However,because of the complex interaction of land and climate,retrieval of Ta from the LST is still far from straightforward.The estimation accuracy varies greatly depending on the model,particularly for maximum Ta.This study estimated monthly average daily minimum temperature(Tmin),average daily maximum temperature(Tmax)and average daily mean temperature(Tmean)over the Loess Plateau in China based on Moderate Resolution Imaging Spectroradiometer(MODIS)LST data(MYD11A2)and some auxiliary data using an artificial neural network(ANN)model.The data from 2003 to 2010 were used to train the ANN models,while 2011 to 2012 weather station temperatures were used to test the trained model.The results showed that the nighttime LST and mean LST provide good estimates of Tmin and Tmean,with root mean square errors(RMSEs)of 1.04℃ and 1.01℃,respectively.Moreover,the best RMSE of Tmax estimation was 1.27℃.Compared with the other two published Ta gridded datasets,the produced 1 km×1 km dataset accurately captured both the temporal and spatial patterns of Ta.The RMSE of Tmin estimation was more sensitive to elevation,while that of Tmax was more sensitive to month.Except for land cover type as the input variable,which reduced the RMSE by approximately 0.01℃,the other vegetation-related variables did not improve the performance of the model.The results of this study indicated that ANN,a type of machine learning method,is effective for long-term and large-scale Ta estimation.

Absorptive root-multidimension strategy links air temperature and species distribution in a montane forest

Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorptive root traits. Seven functional traits of the absorptive roots of 240 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient on Mt. Fanjingshan, Tongren City, Guizhou, and then the direct and indirect effects of these controls on species distribution were detected.Results: Absorptive roots adapted to air temperature with two strategies. The first strategy was positively associated with the specific root area(SRA) and specific root length(SRL) and was negatively associated with the root tissue density(RTD), representing the classic root economics spectrum(RES). The second strategy was represented by the trade-off between root diameter, mycorrhizal fungi colonization(MF) and SRL, representing the collaboration gradient with “do it yourself” resource uptake ranging from “outsourcing” to mycorrhizal resource uptake. Air temperature regulated species distribution in six ways: directly reducing species importance value;indirectly increasing the species importance value by reducing soil nitrogen content or increasing soil pH by reducing soil moisture inducing absorptive roots to change from “do it yourself” resource absorption to “outsourcing” resource absorption;indirectly decreasing the species importance value by decreasing soil moisture to change from“outsourcing”resource absorption to “do it yourself” resource absorption;indirectly increasing the species importance value with increasing soil pH by reducing soil moisture resulting in absorptive root traits turning into nutrient foraging traits;and indirectly decreasing the species importance value by promoting absorptive root traits to nutrient conservation traits.Conclusions: Absorptive root traits play a crucial role in the regulation of species distribution through multiapproaches of air temperature.

Low ambient temperature and air pollution are associated with hospitalization incidence of coronary artery disease:Insights from a cross-sectional study in Northeast China

Background:Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease(CAD).However,there remains a need to explore and clarify the evidence for associations between meteorological changes and hospitalization incidences related to CAD and its subtypes,especially in cold regions.This study aimed to systematically investigate the relationship between exposure to meteorological changes,air pollutants,and hospitalization for CAD in cold regions.Methods:We conducted a cross-sectional study using hospitalization records of 86,483 CAD patients between January 1,2009,and December 31,2019.Poisson regression analysis,based on generalized additive models,was applied to estimating the influence of hospitalization for CAD.Results:Significant associations were found between low ambient temperature[-10℃,RR=1.65;95%CI:(1.28-2.13)]and the incidence of hospitalization for CAD within a lag of 0-14 days.Furthermore,O_(3)[95.50μg/m^(3),RR=12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.Furthermore,O_(3)[95.50μg/m^(3),RR=1.12;95%CI:(1.03-1.21)]and NO_(2)[48.70μg/m^(3),RR=1.0895%CI:(1.01-1.15)]levels were identified as primary air pollutants affecting the incidence of CAD,ST-segment-elevation myocardial infarction(STEMI),and non-STEMI(NSTEMI)within the same lag period.The effect curve of CAD hospitalization incidence significantly increased at lag days 2 and 4 when NO_(2)and O_(3)concentrations were higher,with a pronounced effect at 7 days,dissipating by lag 14 days.No significant associations were observed between exposure to PM,SO_(2),air pressure,humidity,or wind speed and hospitalization incidences due to CAD and its subtypes.Conclusion:Our findings suggest a positive correlation between short-term exposure to low ambient temperatures or air pollutants(O_(3)and NO_(2))and hospitalizations for CAD,STEMI,and NSTEMI.These results could aid the development of effective preparedness strategies for frequent extreme weather events and support clinical and public health practices aimed at reducing the disease burden associated with current and future abnormal weather events.

Design and Implementation of Batch Calibration System for Platinum Resistance Temperature Sensors

Developing a calibration and collection system of platinum resistance temperature sensor using Python language environment can read the information returned by the serial port and automatically generate an"Temperature Sensor Calibration Record Table"excel table with the current date as the file name.It can collect data from 10 platinum resistance temperature sensors at once,achieving automation and improving work efficiency.

Rainfall and Temperature Variations in a Dry Tropical Environment of Nigeria

This study examines long-term rainfall and temperature variations over a dry tropical environment in Nigeria.An assessment of the variations of these weather variables showcases the extent of climate change limits and corresponding effects on the biotic environment.Rainfall and temperature data were obtained from Nigerian Meteorological Agency for a period of 31 years(1991-2020)for Kano and Katsina States.Descriptive statistics were used to determine the degree of variability of the weather variables across spatial domains.Results showed that there is a sharp contrast in mean annual rainfall amounts of 1154.1 mm and 569.6 mm for Kano and Katsina located in the dry continental and semi-arid climate zones of Nigeria respectively.It is revealed that the month of August had the highest mean monthly rainfall for both areas i.e.359 mm and 194 mm with little or no trace during the dry season.The sharp difference in rainfall amount across spatial domains of the near similar climate zones shows that the Inter-tropical Discontinuity(ITD)does not completely overwhelm the northern band of Nigeria in August.The least variable monthly rainfall was in August and July with coefficient variations(CV)of 40%and 47%for Kano and Katsina.The months of February and March had the highest CV of 557%and 273%for the respective areas.In the examined areas the wet and dry seasons are from June-September and October-May respectively.The index of rainfall variability and drought intensity for the areas ranged from 0.85-0.95 and 45%indicating moderate variability and drought respectively.Mean annual temperature values are 33.4℃and 33.8℃for Kano and Katsina.The study recommends a proper climate observing scheme,most especially for agrarian practices so as to ensure profitable outputs for human sustainability.

On the long-term memory characteristic in land surface air temperatures:How well do CMIP6 models perform?

利用去趋势涨落分析(DFA)方法计算序列的长程记忆性(LTM),以CRUTEM5数据集的结果作为观测参照,评估了60个参与第六次国际耦合模式比较计划(CMIP6)的气候模式对地表气温LTM的再现能力.结果表明:大部分模式可以再现全球平均地表气温序列的LTM特征,其中AWI-ESM-1-1-LR和E3SM-1-0的模拟效果最好;60个模式均能模拟LTM随纬度带的变化;综合来说,全球水平上CNRM-CM6-1和HadGEM3-GC31-LL对地表气温LTM的模拟性能最好;多模式平均相比单一模式模拟性能更好;多模式平均与观测结果的偏差以及模式之间的模拟差异显著体现在赤道和沿海区域,这种偏差可能源于模式对海气耦合过程的模拟差异.

严寒地区混合垂直通风猪舍环境质量评价

为探究垂直通风系统(屋顶与粪坑混合排风)在寒区猪舍中的适应性,该研究在秋冬季节对内蒙古某规模化猪舍的热湿与空气质量环境进行了实时连续监测,并根据测试结果对猪舍环境质量进行评价。结果表明:1)测试期间,舍内平均温度、相对湿度以及氨气(NH_(3))、二氧化碳(CO_(2))、总悬浮颗粒物(total suspended particulate, TSP)浓度分别为22.7℃、59.6%、6.5 mg/m^(3)、2 200 mg/m^(3)、2 915μg/m^(3),舍内通风量为0.34~0.39 m^(3)/(h·kg),各环境指标基本满足生产环境阈值要求;保育期间舍内有效环境温度范围为27.1~30.7℃,存在轻度热应激情况,占总监测时间的12.9%;2)舍内温度、相对湿度与NH_(3)、CO_(2)、TSP浓度空间分布不均匀系数分别为0.01、0.15、0.45、0.03、0.15,各环境参数空间分布均较为均匀;3)试验单元(U1、U3)猪的平均日增质量、料重比与死淘率分别842和818 g/d、2.68和2.79、1.68%和1.31%,生产性能良好。综上,不设吊顶的侧墙进风,屋顶与粪坑混合排风的垂直通风系统,总体上能够满足严寒地区猪舍秋冬季热湿环境与空气质量调节需求,保证良好的生产性能。

杭州国家版本馆恒温恒湿空调系统设计

介绍了恒温恒湿库房空调系统的设计,提出了可在库房建成初期、运行稳定期、战时等灵活切换的3种运行模式,分析了其各自的处理过程与节能性;给出了平、战时空调系统选择方案,提出了平时回收空气源热泵机组和冷水机组的冷凝热作为再热热源,战时利用新风预冷实现温湿度独立控制的方法;利用CFD模拟对室内气流组织进行了优化设计;提出了采用含湿量控制代替定露点法进行湿度控制和风机变频等控制策略。通过调试与运行,证明了各项设计措施在项目中应用的有效性。