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 °C and 33.8 °C 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.

The disposal of solid waste close to water bodies is becoming a threat to the potability of water and the survival of aquatic organism. This research work was carried out to assess the impact of solid waste disposal on Nwaorie River in Owerri, Imo State, Nigeria. This was to ascertain the level of some heavy metals and physico-chemical parameters that could affects the quality of the water. Three sampling stations were established along the length of the study area and water from untreated effluent discharged points, 50m upstream, 50m midstream and 50m downstream respectively from the point of discharge. The water sample collected was taken to the Laboratory for analysis. Parameters such as pH, turbidity, Temperature, Total Dissolved Solid, Electrical conductivity, Dissolved Oxygen, Zinc, Arsenic, Iron, Cadmium were measured in situ using a multi-parameter water quality monitor and flame absorption spectrometry. The results obtained revealed the concentration of dissolved Oxygen ranged 6.900-7.400mg/l, Biochemical Oxygen Demand ranged 0.250-0.540mg/l, mean of pH has the highest value of 5.30±0.0 at the downstream, electrical conductivity highest value was 98.00±0.0 at the downstream and temperature was found highest at the upstream with a value of 31.2±0.01 Zinc was less than 0.003mg/l in all sampling points, Iron, zinc and Arsenic were not detected while CaCO₃ ranged 13-29mg/l and turbidity was 0.00. When compared the results of the measured parameters with World Health Organization Standard, all the measured parameter fell within the permissible limit. The study therefore concluded that river Nwaorie is slightly impacted by untreated waste deposited within the vicinity of the river, which could have implications for people that depend on the river for domestic uses and also aquatic organism in the river. Measures should therefore, be taken to stop this unhealthy way of waste disposal.

Sustainable forest bioeconomy (SFB), as a multidimensional approach for establishing mutual benefits between forest ecosystems, the environment, the economy, and humans, is a nature-based solution for a promising future. The study aims to evaluate the potential of carbon stocks (Cstocks) and variability for SFB. It is hypothesized that the decrease in Cstocks is related to an increase in population and agriculture, which caused a decrease in forest area and growing stock and consequently affected SFB. Primary and secondary data were collected from the field, national, and international databases, and analyzed using some statistical and geospatial software packages including IBM SPSS 29.0, CANOCO 5.0, and ArcGIS 10.5. The results revealed that large forest areas were converted to arable lands between 2000 and 2020. Across the forest zones, the aboveground and belowground Cstocks varied significantly, with the aboveground biomass being higher than the belowground biomass. The main drivers of Cstocks were politics and governance (57%), population growth (50%), soil degradation practices (50%), and socio-cultural beliefs (45%). Cstocks had significant negative correlation with population growth, carbon emissions, forest growing stock, forest loss, and the use of forest for biofuel. Evergreen forest zones (rainforest and moist) had more Cstocks than the moist deciduous and swamp/mangrove forests. The study demonstrated that the variability in Cstocks over the last three decades is attributed to an increase in population and agriculture, but Cstocks variability between the forest-vegetation belts could be better explained by differences in trees abundance than population. The study also revealed that the increase in Cstocks contributed to the realization of many SDGs, especially SDG 1, 2, 3, 6, 7, 11, 12, 13, and 15, which in turn support a sustainable forest bioeconomy. Future study is necessary to evaluate Cstocks in individual tree species, biodiversity, and other forest ecosystem services to promote SFB in the country.

Assessment of heavy metal contamination of soils in mechanic workshop at Nekede and Orji, Imo State was carried out using triplicate soil samples at depths of 0 – 15 cm from three sampling points and a control sample - sample point 1 (SP) 20m away from (SP2) and 40m from (SP 3), control point, 1km away from each of the automobile workshops. A total of twelve (12) solil samples were collected using a soil auger. The soil samples were analysed for the following heavy metals (Lead, Copper, Zinc and Nickel) using AA Atomic Absorption Spectrophotometer. Data generated were subjected to statistical analysis such as means and Standard deviation using least significant difference (LSD). Results showed lower concentrations of the heavy metals in soil from control point as compared to soil samples collected from mechanic workshops. Across the sampling point, Zn, Pb, Cu and Ni had concentrations 1.75-89 mg/kg, 1.15-51.15 mg/kg, 0.55-29.35 mg/kg and 0.3-4 mg/kg respectively. Mean concentrations of Zn (49.27 mg/kg), Pb (23.70 mg/kg), Cu (18.25 mg/kg) and Ni (3.58 mg/kg) were higher in the soil samples from auto workshops of Orji compared to Nekede. Across the different sampling points, both Zn (89 mg/kg) and Pb (15.36 mg/kg) were higher in Nekede SP 1 whereas Cu (29.35 mg/kg) and Ni (4 mg/kg) were higher in Orji SP 1 and SP 2 respectively. Assessment of the extent of lead contamination / pollution showed that Zn contamination ranged from very slight Pb varied from very slight, moderate, Cu ranged from low- very low concentration, while Ni varied from very slight’ slight. The study therefore, recommends the control and supervision in the use of land allocated as mechanic workshop to reduce the accumulation of heavy metals.

This work aimed at appraising the changes and responses of soil organic carbon (SOC) stocks to the dynamics in agriculture and other land use between 2001–2030 in São Paulo State, Brazil. This is the first time a study of this kind was conducted at State-scale and in Brazil based on a long-term dataset. Also, the first time the application of InVEST model in land use-carbon dynamics studies was performed in a State-scale. InVEST provides the potential to integrate carbon stocks from other soil components (e.g., biogenic sources) than other models. Soil data were sourced from Soilgrid, and Brazilian soil legacy data. Land use-cover data were collected from the Brazilian Institutes (IBGE and MapBiomas), which was classified into 13 classes including cropland, and others. The result revealed that cropland increased by approx. 70,000–90,000 km² (i.e., 20% increase), forest increased by approx. 20,000–45,000 km² (i.e., 15% increase), while other land use either decreased or had insignificant increase. Regarding SOC stocks, the decadal changes in SOC stocks between 2001–2010, 2010–2020, and 2020–2030 were respectively 1.88 t ha⁻¹ (7.1%), 0.71 t ha⁻¹ (2.5%), and 0.95 t ha⁻¹ (3.3%) for forests, and 1.66 t ha⁻¹ (78.7%), 1.51 t ha⁻¹ (40.1%), and 3.17 t ha⁻¹ (60%) for croplands. Forest had the highest percentage of SOC per hectare (30.07%), but in terms of decadal changes in SOC stocks, cropland had the highest rates of positive increase (i.e., 6.34%). Consequently, these SOC accumulations have helped to mitigate climate change by storing C and reducing atmospheric CO₂. Therefore, this research would provide a vital insight into farming and policymaking on climate change-agriculture sustainability initiatives as a valuable foundation to optimize organized efforts for promoting SOC stocks without compromising environmental safety and food security.