Search Results (35)

As a critical ecologicalbarrier in the semi-arid to semi-humid transition zone of northern China, the interaction between afforestation and climatic stressors in the Yellow River Basin constitutes a pivotal scientific challenge for regional sustainable development. However, the synthesis effects of afforestation and climate on primary productivity require further investigation. Integrating multi-source remote sensing data (2000–2020), meteorological observations with the Standardized Precipitation Evapotranspiration Index (SPEI) and an improved CASA model, this study systematically investigates spatiotemporal patterns of vegetation net primary productivity (NPP) responses to extreme drought events while quantifying vegetation coverage’s regulatory effects on ecosystem drought sensitivity. Among drought events identified using a three-dimensional clustering algorithm, high-intensity droughts caused an average NPP loss of 23.2 gC·m⁻² across the basin. Notably, artificial irrigation practices in the Hetao irrigation district significantly mitigated NPP reduction to −9.03 gC·m⁻². Large-scale afforestation projects increased the NDVI at a rate of 3.45 × 10⁻⁴ month⁻¹, with a contribution rate of 78%, but soil moisture competition from high-density vegetation reduced carbon-sink benefits. However, mixed forest structural optimization in the Three-North Shelterbelt Forest Program core area achieved local carbon-sink gains, demonstrating that vegetation configuration alleviates water competition pressure. Drought amplified the suppressive effect of afforestation through stomatal conductance-photosynthesis coupling mechanisms, causing additional NPP losses of 7.45–31.00 gC·m⁻², yet the April–July 2008 event exhibited reversed suppression effects due to immature artificial communities during the 2000–2004 baseline period. Our work elucidates nonlinear vegetation-climate interactions affecting carbon sequestration in semi-arid ecosystems, providing critical insights for optimizing ecological restoration strategies and climate-adaptive management in the Yellow River Basin. Full article

Faced with the current challenges of the energy transition and the quest for sustainable materials, biobased materials are attracting growing interest for their environmental and thermal properties. Cob is well known for regulating humidity and improving thermal comfort in buildings. A building’s thermal inertia can be increased by integrating phase-change materials (PCMs), enabling energy storage. This study explores the integration of microencapsulated PCMs into biobased materials considering realistic environmental conditions during experimental tests. The results show a homogeneous thermal distribution with low temperature variation at different locations. The relative humidity results confirm a one-dimensional thermal and hygroscopic distribution. The material with PCMs exhibits better thermal regulation. It retains more heat on the outside and reduces indoor temperature variations, improving thermal insulation. Measurements show that PCM integration contributes to reducing wall thermal conductivity and increases its thermal capacity, reaching 2.6 times during phase transition. The simulation is conducted with real 96 h Normandy climate data (January and August) for conventional and biobased walls incorporating PCMs. The results show that winter heat losses are highest for conventional walls (−44.08 kWh/m²), low for cob walls (−24.17 kWh/m²), and lowest for cob walls with PCMs (−13.17 kWh/m²). In summer, all walls exhibit the lowest heat gain, while adding PCMs stabilizes heat flux, reducing peak summer heat flux from 150 W/m² to 50 W/m². The results show that the addition of PCMs significantly improves thermal and hygroscopic performance. Full article

Diseases in pig houses not only hinder the growth and productivity of pigs but also result in significant economic losses for farmers due to high mortality rates. Although viral infections, including PRRS and PCV-2, are the primary causes, the likelihood of disease onset is closely linked to the pigs’ immune status, which is often compromised by environmental stressors. This study aimed to investigate the relationship between environmental conditions and pig mortality through detailed field monitoring in a commercial pig house with 600 growing pigs. The facility, which experienced a surge in mortality after a ventilation system change, was analyzed for various environmental parameters, including ammonia concentration (range: 7.0–10.7 ppm), dust levels (PM10: 106 µg/m³, PM2.5: 45 µg/m³), ventilation rates (0.49 AER, 67% of design capacity), air temperature (mean: 22.3 °C, range: 18.1–28.7 °C), and relative humidity (mean: 67.4%, range: 55.3–83.2%). Pig mortality and its spatial distribution were recorded, while viral infections were identified using RT-PCR, detecting pathogens such as PRRS, PCV-2, Mycoplasma hyopneumoniae, and Salmonella. Our findings revealed that although dust and ammonia concentrations remained within permissible limits, mortality was significantly correlated with thermal instability. Chronic respiratory diseases were observed in regions where ventilation was concentrated, resulting in daily temperature variations as high as 6.64 °C. The combination of improper ventilation and frequent temperature fluctuations weakened the pigs’ immunity, facilitating the onset of disease. This research underscores the critical role of maintaining stable microclimatic conditions in reducing mortality and highlights the need for advanced automated environmental control systems in smart livestock barns. The insights gained from this study provide a foundational framework for developing precision ventilation and thermal management strategies to enhance productivity and animal welfare. Full article

The accurate prediction of heat demand in retrofitted residential buildings is crucial for optimizing energy consumption, minimizing unnecessary losses, and ensuring the efficient operation of heating systems, thereby contributing to significant energy savings and sustainability. Within the framework of this article, the dependence of the energy consumption of a thermo-modernized building on a chosen set of climatic factors has been meticulously analyzed. Polynomial fitting functions were derived to describe these dependencies. Subsequent analyses focused on predicting heating demand using artificial neural networks (ANN) were adopted by incorporating a comprehensive set of climatic data such as outdoor temperature; humidity and enthalpy of outdoor air; wind speed, gusts, and direction; direct, diffuse, and total radiation; the amount of precipitation, the height of the boundary layer, and weather forecasts up to 6 h ahead. Two types of networks were analyzed: with and without temperature forecast. The study highlights the strong influence of outdoor air temperature and enthalpy on heating energy demand, effectively modeled by third-degree polynomial functions with R² values of 0.7443 and 0.6711. Insolation (0–800 W/m²) and wind speeds (0–40 km/h) significantly impact energy demand, while wind direction is statistically insignificant. ANN demonstrates high accuracy in predicting heat demand for retrofitted buildings, with R² values of 0.8967 (without temperature forecasts) and 0.8968 (with forecasts), indicating minimal performance gain from the forecasted data. Sensitivity analysis reveals outdoor temperature, solar radiation, and enthalpy of outdoor air as critical inputs. Full article

Ammonia (NH₃) is a major pollutant in poultry farms, negatively impacting bird health and welfare. High NH₃ levels can cause poor weight gain, inefficient feed conversion, reduced viability, and financial losses in the poultry industry. Therefore, accurate estimation of NH₃ concentration is crucial for environmental protection and human and animal health. Three widely used machine learning (ML) algorithms—extreme learning machine (ELM), k-nearest neighbor (KNN), and random forest (RF)—were initially used as base algorithms. The wavelet transform (WT) with ten levels of decomposition was then applied as a preprocessing method. Three statistical metrics, including the mean absolute error (MAE) and the correlation coefficient (R), were used to evaluate the predictive accuracies of algorithms. The results indicate that the RF algorithms perform robustly individually and in combination with the WT. The RF-WT algorithm performed best using the air temperature, relative humidity, and air velocity inputs with a MAE of 0.548 ppm and an R of 0.976 for the testing dataset. In summary, applying WT to the inputs significantly improved the predictive power of the ML algorithms, especially for inputs that initially had a low correlation with the NH₃ values. Full article

This study aimed to investigate the effects of different humidity levels on the growth performance, slaughter performance, and meat quality of Pekin ducks through the artificial control of humidity, and to identify the suitable environmental humidity for Pekin duck growth. A completely randomized single-factor design was employed, selecting 144 newly hatched male Pekin ducks with healthy and similar BW (body weight) (60.92 g ± 4.38). These ducks were randomly assigned to four groups (A (RH (relative humidity) = 60%), B (RH = 67%), C (RH = 74%), D (RH = 81%)), with 12 ducks and 3 replicates in each group. The ducks were raised in a climate-controlled room for 42 days with ad libitum access to feed and water. BW and feed intake were measured every 3 days, and slaughter performance and meat quality were assessed at 42 days. There was no significant difference in the ADG (average daily gain) from 1 to 21 days (p > 0.05). The ADFI (average daily feed intake) of Group D was significantly lower than that of Groups A, B, and C (p < 0.05), with no significant differences between Groups A, B, and C (p > 0.05). At 42 days, the BW, ADG, and ADFI of Groups A and C were significantly higher than those of Group D (p < 0.05), with no significant differences among Groups A, B, and C (p > 0.05). Group C had a significantly higher breast muscle weight, breast muscle ratio, liver weight, and liver index than Groups B and D (p < 0.05), with no significant differences between Groups A, B, and D (p > 0.05). The meat shear force in Group C was significantly lower than that in Groups A, B, and D (p < 0.05). The L* (brightness) of Group C was significantly lower than that of Group A (p < 0.05), and the a* (redness) value of Group C was significantly higher than that of Groups A and B (p < 0.05), with no significant difference compared to Group D (p > 0.05). Group B had a significantly higher cooking loss than Groups A, C, and D (p < 0.05), with no significant differences among Groups A, C, and D (p > 0.05). Under 26 °C conditions, Pekin ducks perform best in terms of the production performance and feed efficiency, with high-quality meat, especially when reared at 74% humidity. Full article

As building energy consumption gains ever-increasing attention worldwide, the focus on addressing it through the examination and optimization of efficient heat recovery solutions continues to intensify. With well-insulated and airtight buildings, the proportion of heating needs attributed to ventilation is growing, leading to the widespread integration and optimization of heat recovery solutions in mechanical ventilation systems. Heat recovery in ventilation is a highly efficient strategy for reducing heat losses and conserving energy. This study involves the investigation of a ventilation unit installed in an apartment situated in Riga, Latvia, as a practical examination of heat recovery system efficiency within the Latvian climate conditions, representing a cold climate region. The objective of this study was to examine the heat recovery efficiency of the ventilation system in the Latvian climate with variable outdoor and exhaust air parameters, given that the dry heat recovery efficiency is different from the actual heat recovery efficiency. The ventilation unit was equipped with a plate heat exchanger at an airflow rate of 105 m³/h. To evaluate heat recovery efficiency, extensive measurements of air temperature and relative humidity were conducted. The collected data was analyzed, employing statistical regression analysis to ensure measurement reliability and assess correlations. The findings indicated a strong correlation between variables such as heat content, moisture content, and sensible air parameters. It was observed that the actual heat recovery efficiency was 6% higher than the calculated dry efficiency, emphasizing the importance of considering real-world conditions in heat recovery assessments. Additionally, regression analysis demonstrated a positive linear correlation with a coefficient of 0.77, highlighting the dependency between actual measurements and the theoretical model. These quantitative outcomes provide essential insights for optimizing heat recovery systems and enhancing energy-efficient ventilation practices, especially in cold climate environments. Moreover, this study highlights the strong correlation between variables such as heat content, moisture content, and sensible air parameters. Findings offer essential insights for optimizing heat recovery systems and enhancing energy-efficient ventilation practices, especially in cold climate environments. Full article

Proton exchange membrane fuel cells are gaining increasing importance in vehicle applications. The exhaust gas composition regarding the water and oxygen content and the mass flow are important parameters in fuel cell research (e.g., for designing the test bed, quantifying the hydrogen loss in the exhaust, performing experiments with air pollutants, and monitoring degradation). The exhaust gas composition is also important for vehicle applications (e.g., ensuring safe hydrogen levels in the exhaust). Performing direct measurements of the exhaust mass flow and the relative humidity is challenging due to the high-humidity environment. This article presents a mathematical thermodynamic model used to calculate the exhaust gas mass flow and relative humidity, validated by balancing the gas species composition between cathode inlet and exhaust and by using data measured at the fuel cell system test bed. Four calculation model variations and their analyses are discussed. Furthermore, the exhaust gas composition throughout the fuel cell system operating range is presented. The results of air pollutant experiments provide comprehensive examples for the application of the calculation model. These results demonstrate the suitability of the model for its application in fuel cell system research. Full article

The high environmental temperature is one of the main factors challenging the broiler industry during the hot seasons due to it causing more thermal stress. This study aimed to find the effects of heat stress under hot arid environments on the growth performance, carcass traits, and nutritional composition of breast meat in broiler chickens. A total of 240 broiler chickens were allocated into two groups: (1) a control group (thermoneutral environment (TN); 24 ± 0.17 °C) and (2) a heat stress (HS) group, with 30 replicates in each environment. From d 25 to 35 of age, the broiler chickens in the HS group were exposed to 8 h/day of thermal stress (34 ± 0.71 °C) from 8:00 am to 4:00 pm, while the actual recorded value of ambient temperature was 31 °C on average with a relative air humidity (RH) between 48 and 49% for 10 consecutive days (d 25–35 of age). The live body weight (BW), weight gain, and feed intake significantly deteriorated (p < 0.05), and the feed conversion ratio tended to deteriorate (p = 0.055) in the HS group. The hot and cold carcass yields increased (p < 0.05), while the relative heart and liver weights decreased (p < 0.05) in the broiler chickens exposed to HS. The breast meat yield tended to decrease (p = 0.057), while wing meat yields increased significantly (p = 0.050) in heat-stressed broiler chickens. The shrinkage of the carcass percentage increased during chilling (p < 0.001) in the HS group. The ultimate pH values; cooking loss; and contents of moisture, crude protein, and fat of breast meat showed no response (p > 0.05) between the TN and HS groups. The heat-stressed broiler chickens presented lower levels of arachidonic acid (C20:4 (n-6)) (p = 0.01) and eicosadienoic acid (C20:2 (n-6)) (p = 0.050) in the breast meat, while the variations in n-3 polyunsaturated fatty acid were insignificant (p > 0.05) between the groups. In conclusion, our findings confirmed that the hot arid environments could reduce the production performance of broiler chickens and increase carcass shrinkage during chilling, but did not compromise the n-3 polyunsaturated fatty acid and cooking loss in the breast meat. Full article

After being harvested, fresh apples and apricots have a high moisture content and are put through a drying process to reduce waste and lengthen shelf life. This study intends to evaluate the physicochemical parameters during moisture removal and product heating in order to conduct an experimental investigation of the convective drying of apples and apricots in a pilot drying installation. The drying agent’s temperature and/or speed can be adjusted using the pilot installation. About the raw materials: the apricots (Neptun variety) were dried and cut into halves, while the apples (Golden Delicious variety) were dried and cut into 4 mm thick slices. The fruits’ drying properties were observed at 50 °C, 60 °C, 70 °C, and 80 °C, air speeds of 1.0, 1.5, and 2.0 m/s, and relative air humidity levels of 40–45%. Findings of the ascorbic acid content, color, heating, and dimensional fluctuations are provided and examined. Increased air velocity and temperature had the expected effect of increasing water loss, solid gain, and shrinking. Depending on the drying conditions, different color characteristics were applied. Full article

In Niger (a fully Sahelian country), the use of climate information is one of the early warning strategies (EWSs) for reducing socio-economic vulnerabilities in farmer communities. It helps farmers to better anticipate risks and choose timely alternative options that can allow them to generate more profit. This study assesses the impacts of the use of climate information and services that benefit end-users. Individual surveys and focus groups were conducted with a sample of 368 people in eight communes in Southwestern Niger. The survey was conducted within the framework of the ANADIA project implemented by the National Meteorological Direction (NMD) of Niger. The survey aims to identify different types of climate services received by communities and evaluates the major benefits gained from their use. Mostly, the communities received climate (73.6%) and weather (99%) information on rainfall, temperature, dust, wind, clouds, and air humidity. Few producers in the area (10%) received information on seasonal forecasts of the agrometeorological characteristics of the rainy season. The information is not widely disseminated in the villages during the roving seminars conducted by the NMD. For most people, this information is highly relevant to their needs because of its practical advice for options to be deployed to mitigate disasters for agriculture, livestock, health, water resources, and food security. In those communities, 82% of farmers have (at least once) changed their routine practices as a result of the advice and awareness received according to the climate information. The information received enables farmers (64.4%) to adjust their investments according to the profile of the upcoming rainfall season. The use of climate information and related advice led to an increase of about 64 bunches (equivalent to 10 bags of 100 kg) in annual millet production, representing an income increase of about 73,000 FCFA from an average farmland of 3 ha per farmer. In addition, the use of climate information helps to reduce the risks of floods and droughts, which often cause massive losses to crop production, animal and human life, infrastructure, materials, and goods. It has also enabled communities to effectively manage seeds and animal foods and to plan social events, departures and returns to rural exodus. These analyses confirm that the use of climate information serves as an EWS that contributes to increasing the resilience of local populations in the Sahel. Full article

Transportation is a major sector of energy consumption in most, if not in all, European countries. Besides the energy used for traction, energy is also consumed for ventilation, heating, and cooling inside the vehicles to assure traveler comfort. This issue gains increasing importance as the demand for public transport increases in the future. There is a need for retrofit to improve the thermal resistance of the envelope of existing vehicles to reduce the heat loss to the environment during the cold period of the year, especially in the Alpine region. A major concern in adding insulation material to the envelope is the possibility of convective moisture transfer due to air circulation in the vehicle, which would cause condensation accumulation on the cold surfaces. The present investigation addresses this topic by measuring surface and air temperature, air moisture, air flow, and heat flow at several critical locations of a vehicle during its travel in the Swiss Alpine region over several months during the cold period of the year. Temperature measurements showed the potential of reducing the heat losses in some parts of the vehicle. The level and duration of the moisture exposure did not suggest a relevant formation of condensation in the cross-section of the vehicle wall. The observed increase in relative humidity when driving through tunnels is too short to cause relevant condensation in the vehicle shell. The measured low air flow justifies the assumption that no forced convection occurs in the envelope cavities. Full article

The utilization of production systems with reduced chemical input renewed the interest in Ustilago nuda and Pyrenophora graminea. The investigations of seed fungicide treatments are more related to their efficacy than to their contribution to yield gain. The data were collected from research and development trials on fungicide efficacy against U. nuda and P. graminea conducted from 2014 to 2020 in Serbia. Partial least squares, multiple stepwise regression and best subset regression were used for statistical modeling. The total number of plants infected with U. nuda and P. graminea per plot differed significantly in the seven-year period. Shifts in the predominance of one pathogen over the other were also shown. Temperature, total rainfall and relative humidity in flowering time (p < 0.001) influenced the occurrence of both pathogens. The strongest impact on yield loss was observed for temperature in the phenological phases of leaf development (p = 0.014), temperature in flowering time (p < 0.001) and total number of plants infected with U. nuda and P. graminea per plot (p < 0.001). Our results indicated that regression models consisting of both biotic and abiotic factors were more precise in estimating regression coefficients. Neither fungicidal treatment had a stable contribution to yield gain in the seven-year period. Full article

In the present study, genome-wide CNVs were detected in a total of 301 samples from 10 Chinese indigenous horse breeds using the Illumina Equine SNP70 Bead Array, and the candidate genes related to adaptability to high temperature and humidity in Jinjiang horses were identified and validated. We determined a total of 577 CNVs ranging in size from 1.06 Kb to 2023.07 Kb on the 31 pairs of autosomes. By aggregating the overlapping CNVs for each breed, a total of 495 CNVRs were detected in the 10 Chinese horse breeds. As many as 211 breed-specific CNVRs were determined, of which 64 were found in the Jinjiang horse population. By removing repetitive CNV regions between breeds, a total of 239 CNVRs were identified in the Chinese indigenous horse breeds including 102 losses, 133 gains and 4 of both events (losses and gains in the same region), in which 131 CNVRs were novel and only detected in the present study compared with previous studies. The total detected CNVR length was 41.74 Mb, accounting for 1.83% of the total length of equine autosomal chromosomes. The coverage of CNVRs on each chromosome varied from 0.47% to 15.68%, with the highest coverage on ECA 12, but the highest number of CNVRs was detected on ECA1 and ECA24. A total of 229 genes overlapping with CNVRs were detected in the Jinjiang horse population, which is an indigenous horse breed unique to the southeastern coast of China exhibiting adaptability to high temperature and humidity. The functional annotation of these genes showed significant relation to cellular heat acclimation and immunity. The expression levels of the candidate genes were validated by heat shock treatment of various durations on fibroblasts of horses. The results show that the expression levels of HSPA1A were significantly increased among the different heat shock durations. The expression level of NFKBIA and SOCS4 declined from the beginning of heat shock to 2 h after heat shock and then showed a gradual increase until it reached the highest value at 6 h and 10 h of heat shock, respectively. Breed-specific CNVRs of Chinese indigenous horse breeds were revealed in the present study, and the results facilitate mapping CNVs on the whole genome and also provide valuable insights into the molecular mechanisms of adaptation to high temperature and humidity in the Jinjiang horse. Full article

Nowadays, the transformations of cities into smart cities is a crucial factor in improving the living conditions of the inhabitants as well as addressing emergency situations under the concept of public safety and property loss. In this context, many sensing systems have been designed and developed that provide fire detection and gas leakage alerts. On the other hand, new technologies such edge computing have gained significant attention in recent years. Moreover, the development of recent intelligent applications in IoT aims to integrate several types of systems with automated next-generation emergency calls in case of a serious accident. Currently, there is a lack of studies that combine all the aforementioned technologies. The proposed smart building sensor system, SB112, combines a small-size multisensor-based (temperature, humidity, smoke, flame, CO, LPG, and CNG) scheme with an open-source edge computing framework and automated Next Generation (NG) 112 emergency call functionality. It involves crucial actors such as IoT devices, a Public Safety Answering Point (PSAP), the middleware of a smart city platform, and relevant operators in an end-to-end manner for real-world scenarios. To verify the utility and functionality of the proposed system, a representative end-to-end experiment was performed, publishing raw measurements from sensors as well as a fire alert in real time and with low latency (average latency of 32 ms) to the middleware of a smart city platform. Once the fire was detected, a fully automatic NG112 emergency call to a PSAP was performed. The proposed methodology highlights the potential of the SΒ112 system for exploitation by decision-makers or city authorities. Full article