Spatiotemporal Trends in Temperature and Rainfall in Northwestern Vietnam (2009-2024)

This study aimed to analyze data from meteorological stations in central Ukraine that have the longest observation period and to search for patterns in the dynamics of temperature indicators over the past 140-200 years. Data and methods. To characterize the climate of central Ukraine, we analyzed the average monthly and average annual temperatures of Uman, Kropyvnytskyi, and Poltava, which have the longest continuous or almost continuous periods of observation. Based on these data, we have constructed graphs of changes in the average annual and average monthly temperatures for the winter and spring seasons. To analyze the dynamics of temperature indicators, we built linear and 11-year moving averages. The results. The analysis of meteorological data from weather stations in central Ukraine over the entire period of observation showed the following: average annual temperatures increased from 1.4 degrees in Kropyvnytskyi, 1.6 degrees in Uman to 2.5 degrees (since 1886 - 2.2 degrees) in Poltava. The highest average annual air temperatures at all weather stations were recorded in 2020 and 2021. The largest temperature increase occurred in the winter months. Over the entire observation period, the average monthly temperature in December increased by 2.0 degrees in Kropyvnytskyi, 2.3 degrees in Uman, and 3.6 degrees in Poltava (3.3 degrees since 1886). The average monthly temperature in January increased from 2.4 degrees in Uman and Kropyvnytskyi to 4.9 degrees (3.5 degrees since 1886) in Poltava. The average monthly temperature in February increased from 2.2 degrees in Kropyvnytskyi, 3.4 degrees in Uman to 4.1 degrees (since 1886 - 2.9 degrees) in Poltava. All three weather stations have common periods of rising and falling temperatures, with an increase in the average monthly temperature in the winter months from 1987-1989 to 2022. The air temperature in the spring months also increased significantly. Over the entire observation period, the average monthly temperature in March increased from 2.3 degrees in Kropyvnytskyi, 3.0 degrees in Uman to 3.6 degrees (since 1886 - 3.5 degrees) in Poltava. The average monthly temperature in April increased from 2.1 degrees in Kropyvnytskyi, 2.4 degrees in Uman to 4.2 degrees (since 1886 - 3.4 degrees) in Poltava. The average monthly temperature in May increased from 0.5 degrees in Uman and Kropyvnytskyi to 2.9 degrees (since 1886 - 1.3 degrees) in Poltava. All three weather stations have common periods of rising and falling temperatures, with a slight increase in average monthly spring temperatures from 1988-1990 to 2022. Analyzing the graphs of 11-year moving averages, one can notice the presence of periods of increase and decrease in average monthly temperatures lasting about 33 years or doubled periods lasting about 66 years. Scientific novelty. For the first time, the data of weather stations in central Ukraine for the entire period of observation (138 years – Uman, 148 years – Kropyvnytskyi, 198 years – Poltava) were analyzed and regularities in the dynamic of temperature indicators were determined. The practical significance lies in the possibility of using the researchers results to predict future climate change.

Background & Objective: Hand, foot and mouth disease (HFMD) is a contagious disease of children, occurs primarily under five years of age, characterized by a history of brief febrile illness and a typical skin rash over hands and feet with or without sores in mouth, caused usually by Coxsackievirus A16 viruses. It is mainly the disease of tropical and subtropical countries and bears a complex-relation with meteorological variables, like temperature, rainfall and relative humidity, although no study has yet been done in Bangladesh to explain the complex relationship of the disease with these variables. This study sought to describe the occurrence of HFMD and its association with meteorological factors in Dhaka city.
 Methods: The present cross-sectional study collected data of 231 HFMD cases from the records of the daily register of Out-patient Department of Dhaka Shisu Hospital, Dhaka between January 2018 to December 2019. According to the study protocol a child was identified as having HFMD who had a history of brief febrile illness accompanied by a typical skin rash with or without mouth ulcers. Total number of cases treated monthly at OPD during the period were also recorded. Meteorological data were provided by Bangladesh Meteorological Department, which among others, included monthly average temperature, relative humidity and amount of rainfall. While the outcome variable was monthly number of HFMD cases, the predictive variables were average temperature, humidity and rainfall during the study period.
 Result: Majority (85.3%) children in the present study was < 5 years old. A male preponderance was observed in the series (60%) with male to ratio being 3:2. A clustering of HFMD cases was observed to occur between June to October when monthly average temperature, total rainfall and humidity all were at their maximum compared to those found between November to April. The clustering of cases was more intense in the year 2019 than that in the year 2018. During the period average monthly temperature was 29.20C, average rainfall was 62.6% (238 mm) of the total annual precipitation and mean relative humidity was 79%. The proportion of HFMD cases out of total cases treated during the period was 2.2% in 2018 and was 4.1% in 2019, which in the dry season (November to April) was 0.4% and 0.5% in 2018 and 2019 respectively.
 Conclusion: The study concluded that majority of the HFMD cases occur under five years of age and boys are more likely to have the infection than the girls. A seasonality of HFMD occurrence is observed with a higher number of cases occurring in the monsoon season and fewer cases in the dry season. Clustering of HFMD cases occur between May to October when monthly average temperature, total rainfall and humidity all are at peak compared to those in November to April of the year.
 Ibrahim Card Med J 2021; 11 (1): 14-20

Background : Hand, foot and mouth disease (HFMD) is a contagious disease of children, occurs primarily under five years of age, characterized by a history of brief febrile illness and a typical skin rash over hands and feet with or without sores in mouth, caused usually by Coxsackie virus[1]A16 viruses. It is mainly the disease of tropical and subtropical countries and bears a complex-relation with meteorological variables like temperature, rainfall and relative humidity, although no study has yet been done in Bangladesh to explain the complex relationship of the disease with these variables.
 Objective : This study sought to describe the occurrence of HFMD and its association with meteorological factors in Dhaka city.
 Methods : The present cross-sectional study collected data of 231 HFMD cases from the records of the daily register of Out-patient Department of Dhaka Shishu Hospital, Dhaka between January 2018 to December 2019. According to the study protocol a child was identified as having HFMD who had a history of brief febrile illness accompanied by a typical skin rash with or without mouth ulcers. Total numbers of cases treated monthly at OPD during the period were also recorded. Meteorological data were provided by Bangladesh Meteorological Department, which among others, included monthly average temperature, relative humidity and amount of rainfall. While the outcome variable was monthly number of HFMD cases, the predictive variables were average temperature, humidity and rainfall during the study period.
 Results : Majority (85.3%) children in the present study was < 5 years old. A male preponderance was observed in the series (60%) with male to female ratio being 3:2. A clustering of HFMD cases was observed to occur between June to October when monthly average temperature, total rainfall and humidity all were at their maximum compared to those found between November to April. The clustering of cases was more intense in the year 2019 than that in the year 2018. During the period average monthly temperature was 29.20C, average rainfall was 62.6% (238 mm) of the total annual precipitation and mean relative humidity was 79%. The proportion of HFMD cases out of total cases treated during the period was 2.2% in 2018 and was 4.1% in 2019, which in the dry season (November to April) was 0.4% and 0.5% in 2018 and 2019 respectively.
 Conclusions : The study concluded that majority of the HFMD cases occur under five years of age and boys are more likely to have the infection than the girls. A seasonality of HFMD occurrence is observed with a higher number of cases occurring in the monsoon season and fewer cases in the dry season.Clustering of HFMD cases occur between May to October when monthly average temperature, total rainfall and humidity all are at peak compared to those in November to April of the year.
 Northern International Medical College Journal Vol.11 (2) Jan 2020: 453-457

Summary A total of 966 cichlids, Cichlasoma urophthalmus, was sampled from three karstic water bodies (cenotes) in the Yucatan Peninsula. Sex ratio was not different from 1. Specimens with ripe eggs were found during the dry and rainy seasons in the inland cenote and during the dry, rainy, and north winds seasons in the two wetland cenotes. With respect to relative fecundity, data show the C. urophthalmus inland population as two- to three-fold greater (53.1 ± 27.7) than the wetland populations (15.7 ± 5.1 and 18.2 ± 3.1). This is attributable to the different breeding strategies of C. urophthalmus populations inhabiting these two types of cenotes. In particular, the ichthyofauna from the two wetlands showed not only higher species richness (17 and 16 species) but also a higher number of potential predators (nine and eight species) as compared to the inland cenote (six species; two potential predators). It is hypothesized that C. urophthalmus adjusts its clutch size and extends its breeding periods as a response to riskier sites as compared to more secure ones; a higher competition for breeding sites and to increased fishing mortality.

The aim of this study was to compare testosterone concentration, body weight, scrotal circumference and age to penis detachment from days 30 to 240 in young Boer goat males (n = 22) born during the dry (n = 11) and the rainy (n = 11) seasons. In the dry season the parameters varied as follows: body weight from 3.7 ± 1.1 to 34.0 ± 4.7 kg, scrotal circumference from 7.9 ± 0.8 to 25.7 ± 2 cm, and testosterone concentration from 259.4 ± 172.4 to 4613.4 ± 2892 pc/mL. In the rainy season parameters varied as follows: body weight from 9.7 ± 2.3 to 28.1 ± 6.9 kg, scrotal circumference from 9.5 ± 1.5 to 22.0 ± 3.0 cm and testosterone from 521.9 ± 311.3 to 3417.9 ± 2021.8 pc/mL. At three months of age, 70% of animals born during the rainy season presented with penis detachment, compared to 67.6% of animals born during the dry season at five months of age. Penis detachment occurred in all males at four and seven months for animals born in the rainy and dry seasons, respectively. There was a positive correlation between testosterone concentration and body weight in the dry (r = 0.30) and rainy (r = 0.43) seasons, between testosterone and scrotal circumference in the dry (r = 0.42) and rainy (r = 0.52) seasons, and between body weight and scrotal circumference in the dry (r = 0.93) and rainy (r = 0.88) seasons. The animals born during the rainy season showed earlier development in all the evaluated parameters than animals born during the dry season. It was found that scrotal circumference is directly correlated to body weight and testosterone concentration. Keywords : Scrotal circumference, testosterone, young male goats, puberty, sexual maturity

Physicochemical parameters of surface water collected from six different points (P1 to P6) on River Sokoto were analysed during January (Dry Season) and August (Rainy Season), 2014 to determine its water quality using standard methods. The highest temperature of 25.6&#176C was recorded by P1 in dry season while P5 recorded the highest value of 29.2&#176C in rainy season. All the water samples were alkaline in dry season with the highest pH value of 8.50 in P5 and the least value of 8.02 in P6 whereas in rainy season, P1, P2 and P3 were slightly acidic while P5 and P6 were slightly neutral and P4 alkaline. The highest values of 510 μS/cm and 850.3 mg/l were recorded from P4 for electrical conductance and hardness respectively in the rainy season whereas in dry season, P5 and P4 had the highest values of 321 μS/cm and 282.8 mg/l respectively. The highest DO and BOD levels in dry season were 1.7 mg/l and 0.7 mg/l respectively in P1 and the least values were 0.7 mg/l and 0.2 mg/l respectively in P5. But in the rainy season, P6 recorded the highest DO value of 0.1 mg/l while P2 and P5 recorded the least value of 0.07 mg/l. For BOD, P5 had the highest value (2.13 mg/l) while P3 had the least value (0.20 mg/l). For COD, the highest value (230 mg/l) was found in P4 and P6 and the least value (30 mg/l) was found in P1 in dry season while in the rainy season, P2 had the highest COD value (1008 mg/l) and P4 had the least value of 32 mg/l. TDS and TSS values generally were higher in the rainy season than in the dry season due to higher amount of floating particles in the rainy season. While P1 and P6 recorded the highest values (800 mg/l and 700 mg/l respectively) in the rainy season, P4 recorded the least value of 100 mg/l in both seasons. The highest Chloride level was found in P4 in the dry (100 mg/l) and rainy (180 mg/l) seasons with the least level in P2 (35 mg/l) in dry season and in P1 and P2 with the least level of 60 mg/l in the rainy season. The highest concentration of Sulphate in P1 (220 mg/l) in dry season was far above the highest concentration (124 mg/l) in the rainy season whereas highest concentration of Nitrate in dry season in P1 (19.7 mg/l) was somehow below the highest concentration in rainy season in P4 (28.1 mg/l). Phosphate and Ammonia had the highest values of 1.77 mg/l and 0.84 mg/l respectively in P5 in dry season while in rainy season, P6 and P4 had the highest values of 0.22 mg/l and 1.20 mg/l respectively. There was significant seasonal variation in some physicochemical parameters and most of the parameters were within permissible limits, thus, making the water suitable for irrigation purposes.

Context In the tropics, there is a substantial demand for a broader understanding of the impact of supplementation strategies on animal growth. Aims The aim of this study was to evaluate the effects of different concantrate supplementation strategies during the dry, rainy, or both seasons on intake, digestibility, performance, and carcass weight of young Nellore bulls. Methods Twenty-eight young Nellore bulls with an initial average liveweight (LW) of 327 ± 4.2 kg of were used. Animals had ad libitum access to a Urochloa brizantha pasture and a mineral mixture sequentially in dry and rainy seasons. Treatments consisted of the following four concentrate supplementation strategies: (1) no concentrate supplementation (−/−); (2) 8 g/kg LW in rainy season (−/+); (3) 8 g/kg LW in dry season (+/−); and (4) 8 g/kg LW in both dry and rainy seasons (+/+). Key results Forage intake was lesser (P < 0.05) in cattle fed +/+ when contrasted against all other supplementation strategies. In the dry season, concentrate supplementation increased (P < 0.04) LW gain from 0.40 to 0.74 kg/animal.day. Considering performance in both the dry and rainy seasons, all supplementation strategies increased (P < 0.05) total LW gain, hot carcass weight, carcass fat and muscle when compared with the negative control treatment −/−. Bulls receiving +/+ had greater (P < 0.05) total LW gains and hot carcass weights than did −/+ and +/− treatments. Directly contrasting −/+ and +/−, supplementation in the rainy season tended (P < 0.10) to increase total LW gain and hot carcass weights. Conclusions Under the conditions of this experiment, concentrate supplementation decreased forage intake but increased LW gain, hot carcass weight and carcass quality. Concentrate supplementation in both the dry and rainy seasons provided greater LW gain and hot carcass weights than did concentrate supplementation during only the dry or rainy seasons. Concentrate supplementation only during the rainy season produced greater hot carcass weights and LW gains than did concentrate supplementation only during the dry season. Implications To achieve maximum LW gains and hot carcass weights, concentrate supplementation should be provided during both dry and rainy seasons. If supplementation costs are a limiting factor, concentrate supplementation during the rainy season is likely to provide greater LW gains and carcass weights than does concentrate supplementation only during the dry season. However, pasture nutritive value, carcass prices and supplement costs must be evaluated before selecting a supplementation strategy.

ABSTRACTThe seasonal characterization and discrimination of savannahs in Brazil are still challenging due to the high spatial variability of the vegetation cover and the spectral similarity between some physiognomies. As a preparatory study for future hyperspectral missions that will operate with large swath width and better signal-to-noise ratio than the current orbital sensors, we evaluated six Hyperion images acquired over the Estação Ecológica de Águas Emendadas, a protected area in central Brazil. We studied the seasonal variations in spectral response of the savannah physiognomies and tested their discrimination in the rainy and dry seasons using distinct sets of hyperspectral metrics. Floristic and structural attributes were inventoried in the field. We considered three sets of metrics in the data analysis: the reflectance of 146 Hyperion bands, 22 narrowband vegetation indices (VIs), and 24 absorption band parameters. The VIs were selected to represent vegetation structure, biochemistry, and physiology. The depth, area, width, and asymmetry of the major absorption bands centred at 680 nm (chlorophyll), 980, and 1200 nm (leaf water) and 1700, 2100, and 2300 nm (lignin-cellulose) were calculated on a per-pixel basis using the continuum removal method. Using feature selection and multiple discriminant analysis (MDA), we tested the discriminatory capability of these metrics and of their combined use for vegetation discrimination in the rainy and dry seasons. The results showed that the spectral modifications with seasonality were stronger with the savannah woodland-grassland gradient represented by decreasing tree height, basal area, tree density and biomass and by increasing canopy openness. We observed a reflectance increase in the red, red edge, and shortwave (SWIR) intervals towards the dry season. In the near-infrared, the reflectance differences between the physiognomies were smaller in the dry season than in the rainy season. From the 22 VIs, the visible atmospherically resistant index (VARI), visible green index (VIg), and normalized difference infrared index (NDII) were the most sensitive indices to water stress and vegetation cover, presenting the largest rates of changes between the rainy (March) and dry (August) seasons in shrub and grassland areas. Absorption band parameters associated with the lignin-cellulose spectral features in the SWIR increased towards the dry season with great amounts of non-photosynthetic vegetation (NPV) in the herbaceous stratum. The opposite was observed for the 680 nm chlorophyll absorption band and the 980 and 1200 nm leaf water features. In general, the number of selected metrics necessary for vegetation discrimination was lower in the dry season than in the rainy season. The best MDA-classification accuracy was obtained in the dry season using nine VIs (79.5%). The combination of different hyperspectral metrics increased the classification accuracy to 81.4% in the rainy season and to 84.2% in the dry season. This combination added a gain higher than 10% for the classification of shrub savannah, open woodland savannah and wooded savannah.

Vegetative and reproductive growth of subtropical and tropical forests plays an important role in regulating carbon cycle and maintaining food web dynamic balance. Here, we used litterfall and climatic data during 1998–2017 at four evergreen forest sites in southern China to analyze temporal variations of community phenology and their climate drivers. Results show that two southwest forests have unimodal patterns with leaf litterfall peaks during dry season, while two southeast forests have bimodal patterns with the first peaks during rainy season and the second peaks during rainy and dry seasons respectively. Peaks of flower litterfall for the four forests occurred during the transitional period between dry and rainy seasons, while peaks of fruit litterfall appeared either at the end of the rainy season at the two southern sites or in the dry season at the two northern sites. Leaf litterfall correlates significantly positively with preseason maximum temperature at the four sites, but significantly negatively with preseason precipitation at two southwest sites. By contrast, flower and fruit litterfall correlates significantly positively with preseason temperature and precipitation at only three and two sites. Moreover, leaf, flower, and fruit litterfall exhibits a 12‐month cycle, which is consistent with the 12‐month cycle of monthly temperature and precipitation. Flower and fruit litterfall displays also multiyear cycles between 18 and 48 months, however, it is inconsistent with the multiyear cycles of monthly temperature and precipitation. Our study highlights that temperature and precipitation are key factors affecting litterfall variations in different time scales in southern China.Abstract in Chinese is available with online material.

Formulation of the problem. This is the second part of a trilogy dedicated to the analysis of climate indicators in central Ukraine over the entire period of instrumental observations, which analyzes air temperature data from the weather stations of Uman, Kropyvnytskyi, and Poltava. This work addresses issues related to the 13th Sustainable Development Goal, which is to combat climate change and strengthen resilience and adaptation to climate-related hazards and disasters in all countries. The purpose of this study was to analyze data from weather stations in central Ukraine that have the longest period of observation and to find patterns in the dynamics of temperature indicators over the past 140-200 years. Data and methods. To characterize the climate of central Ukraine, we analyzed the average monthly and average annual temperatures of Uman, Kropyvnytskyi, and Poltava, which have the longest continuous or almost continuous period of observation. Based on these data, we have constructed graphs of changes in the average annual and average monthly temperatures for the winter and spring seasons. To analyze the dynamics of temperature indicators, we constructed linear and 11-year moving trends. Results. At all weather stations, there is a trend towards an increase in both average annual air temperatures and temperatures for certain months. In particular, in Uman, the average annual temperature over the entire observation period (138 years) has increased from +6.80C to +8.60C, i.e. by 1.8 degrees. In Kropyvnytskyi, average annual temperatures over 149 years increased from +7.40C to +8.90C, i.e. by 1.5 degrees. In Poltava, the average annual temperature over 199 years has increased from +5.90C to +8.70C, i.e. by 2.8 degrees (since 1886 from +6.40C to +8.70C, i.e. by 2.3 degrees). At all weather stations, the most significant increase in average annual temperatures occurred between 1989 and 2023. Temperatures in the autumn months increased the least. Over the entire observation period, average monthly temperatures in September/October/November increased from 0.3/0.1/0.10C in Uman, 0.6/0.1/1.80C in Kropyvnytskyi to 1.5/1.2/1.90C (since 1886 – 0.9/0.9/1.70C) in Poltava. All three meteorological stations have common periods of temperature increases and decreases, in particular, a decrease in average monthly summer temperatures occurred from 1947-1969 to 1985-1995; from 1986-1996 to 2023, an increase in air temperature. Air temperatures in the summer months have increased quite significantly. Over the entire period of observation, the average monthly temperature in June/July/August increased from 0.9/0.3/0.70C in Kropyvnytskyi, 1.9/1.3/1.60C (since 1886 – 1.3/1.2/1.40C) in Poltava to 2.0/1.1/1.10C in Uman. The greatest increase in average monthly autumn temperatures occurred from 1999-2001 to 2023. Analyzing the graphs of 11-year moving averages, one can see the presence of periods of increase and decrease in average monthly temperatures lasting about 33 years or doubled periods lasting about 66 years. Scientific novelty. For the first time, the data of meteorological stations in central Ukraine for the entire period of observation (138 years – Uman, 149 years – Kropyvnytskyi, 199 years – Poltava) were analyzed and regularities in the dynamics of temperature indicators were determined. The practical significance lies in the possibility of using the results of the study to predict future climate change.

Acid sulfate soil is one of the most serious regional environmental problems after destruction of the peat layer over pyrite-containing sediment after agricultural land development and deforestation. Sulfuric acid discharged from acid sulfate soil causes acidification of river water. In pyrite distributing areas within the lower basin of the Sebangau and Kahayan rivers in Central Kalimantan, the water of the mainstream of the rivers as well as water discharged from canals into the mainstream in the rainy season show much higher acidity and a higher concentration of sulfate ions than in the dry season. The objective of the present study was to obtain information on utilization of natural water from local inhabitants in the basin with water pollution including sulfuric acid contamination. We held interviews with local inhabitants in sulfuric acid polluted areas in Paduran and Pangkoh as well as areas around Sigi village concerning the sources of water and evaluation of water quality in their habitat. Inhabitants around Sigi mostly depended on well water both in the rainy and dry seasons, whereas the sources of drinking water for inhabitants in Paduran and Pangkoh differed significantly between dry and rainy seasons. River water chemistry showed little difference between the dry season and the rainy season in the Sigi area, whereas river and canal water in the rainy season in Paduran and Pangkoh showed lower pH than in the dry season due to a high concentration of sulfuric acid in the rainy season. Accordingly, river and canal water in the rainy season in polluted areas was not available as drinking or cooking water and thus they avoided using river water for drinking or cooking in the rainy season. Although sulfuric acid concentration in river water both in Pangkoh and Paduran were higher in the rainy season than in the dry season, people in Pangkoh evaluated that water in the rainy season to be better than that in the dry season, whereas people in Paduran evaluated that water in the dry season to be better than that in the rainy season. Paduran people would evaluate water quality by SO42- concentration, whereas Pangkoh people would evaluate water quality by salt concentration because of the lower concentration of SO42- of water in Pangkoh in the rainy season than that in Paduran. Pangkoh people recognized that water contaminated with sulfuric acid was much preferable than water contaminated with sea salt, but they avoided using water contaminated with sulfuric acid in the rainy season. More than 70% of the Paduran people answered that river water presents a high risk for drinking and swimming, whereas only 11% or less of the Pangkoh people knew about the risk of sulfuric acid for human health. The Pangkoh people avoided using river water contaminated with sulfuric acid, but the knowledge about sulfuric acid’s effects on human health was not sufficient. Thus we concluded that although selectivity of water was similar for the local inhabitants of the two villages in polluted area, awareness about the risks of sulfuric acid pollution for human health proved to be quite different between the two villages.

The present study aims to analyze the effectiveness of ovitraps in the capture of Hg leucocelaenus eggs and evaluate the influence of the dry and rainy seasons on their abundance and hatching rates. The eggs were collected in the Atlantic Forest of State of Rio de Janeiro, Brazil, an area in which the yellow fever virus is known to circulate. We distributed 15 ovitraps in three sampling points, with five ovitraps per point. We distributed 15 ovitraps in three sampling points on trees within a forested area, which were sequentially numbered, monitored, and replaced every two weeks from October 2016 to April 2018. There was a high dominance of Hg. leucocelaenus eggs (98.4%) and a variation in egg hatching rates between the wet and dry seasons. These rates were 1.5 times higher in the rainy season than in the dry season. The rainy season also showed a greater abundance of eggs and higher values of ovitrap positivity and egg density indexes in the installed ovitraps. The abundances of Hg. leucocelaenus eggs were positively correlated with mean monthly temperature and air humidity but not significantly correlated with accumulated precipitation. These results, as well as their implications for the possible use of ovitraps to monitor vector mosquitoes of yellow fever in the study region, are discussed.

Differentiation analysis of VOCs in Kunming during rainy and dry seasons based on monitoring high temporal resolution

This study was carried out to evaluate the potential nutritive value of commonly found grasses collected at native pasture in West Sumatra, Indonesia during dry and rainy seasons. Variables measured included chemical composition, in vitro digestibility, concentration of Ca, P and Mg, gas production and metabolizable energy (ME) content of the grasses. The results showed that species and season had significant effect on chemical composition and mineral concentration. Crude protein content in the dry season ranged from 6.5% (B. decumbens) to 14.4% (P. maximum) and increased slightly from 7.8% (B. decumbens) to 14. 8% (A. compressus) in the rainy season. Data on fiber fraction showed that grass contained more NDF, ADF and ADL in dry season than in rainy season. Data on mineral concentration showed that C. plectostachyus and P. maximum in dry season had higher Ca than those of other species, while in rainy season P. maximum had highest Ca concentration. In dry season, the DMD varied from 50. 4% (P. purpuphoides) to 59.1% (P. purpureum), while in rainy season ranged from 50.3% (A. gayanus) to 61.8% (P. purpureum). The potential and rate of gas production were significantly (p<0.05) affected by species and season. During dry season, potential of gas production ranged from 21.8 ml/200 mg (A. compressus) to 45.1 ml/200 mg (C. plectostachyus), while in rainy season it varied from 35.6 ml/200 mg (A. gayanus) to 47.5 ml/200 mg (P. purpureum). ME content of grasses varied from 6.0 to 8.3 MJ/kg in dry season and increased slightly from 6.4 to 8.6 MJ/kg in rainy season. Both in dry and rainy seasons, the highest ME content was occurred in P. purpureum and C. plectostachyus. In conclusion, nutritive value of the observed grasses in West Sumatra, Indonesia was relatively higher during rainy season compared with dry season. Pennisetum purpureum and Cynodon plectostachyus had the best nutritive value in both dry and rainy seasons. (Asian-Aust. J. Anim. Sci. 2004. Vol 17, No. 12 : 1663-1668)

In recent years, the earth is burning, whether global warming and its influencing factors, based on time series and gray prediction model, put forward the hypothesis and conclusion, provide the data of various factors, to evaluate the past temperature level, to predict the future global temperature level and its trend and analyze the influencing factors. For problem 1, first, based on the analysis of the global average air temperature data from March 2012-February 2022 and March 2022-October 2022, it is unscientific that the global temperature rise in March 2022 led to a larger rise than in the past 10 years. Second, the ARIMA model and the gray prediction model are used to describe the past global temperature levels and predict the future global temperature levels, respectively. The ARIMA model and the grey prediction model show that the global average annual temperature change has been stable in the past, while the prediction that the average temperature of 20.00°C in 2050 or 2100 is inaccurate. The grey prediction model shows that the global temperature levels will continue to rise in the future, and shows that the average temperature in 2,289 observations is expected to reach 20.00°C. According to the forecast, the global average temperature will not, as long as natural resources are properly used, reach 20.00°C. For problem 2, We first divide the Earth into the southern and northern hemisphere, and second into tropical and southern temperate and northern temperate zones. The linear relationship between global average temperature and the two conditions is discussed separately. According to the results, it significantly shows a strong correlation between the global average temperature and time. If unchecked, the global average temperature will grow over time. Second, using the principal component analysis method shows that may affect the global average temperature in the Middle East energy consumption, global hydropower consumption, world oil consumption, global niobium minerals, the world gas proven reserves, global crude oil production, global cadmium production, and to the results are tested, concluded that the principal component analysis method to influence the main indicators of the global average temperature method is more accurate. Therefore, the suggestions for global temperature change are made: to strive to reduce methane emissions; to further strengthen the strategic deployment and practical actions for energy revolution and low-carbon development, while increasing the intensity of energy low-carbon transformation. For problem 3, We propose the feasibility of this model evaluation and prediction results on slowing down or curbing global warming trends. One is direct emissions reduction, with countries signing contracts to force their carbon emissions and unite against global warming. Reduce heat emissions should be put on everyone's daily living habits, with a limited use of daily necessities, to achieve limited production, limited processing, so as to curb industrial flooding, reduce heat emissions. Second, the indirect emission reduction. With the development of industry, carbon dioxide emissions are constantly increasing, leading to a series of problems such as global warming and sea level rise. Afforestation can absorb the carbon dioxide contained in the atmosphere and reduce the greenhouse gas content in the atmosphere. Therefore, we must realize the importance of afforestation, take appropriate measures to improve the effect of afforestation, and better alleviate global warming.