Objective: This study investigated the relationships between PM_2.5 and 5 criteria air pollutants (SO₂, NO₂, PM₁₀, CO, and O₃) in Heilongjiang, China, from 2015 to 2018 using global and geographically and temporally weighted regression models. Methods: Ordinary least squares regression (OLS), linear mixed models (LMM), geographically weighted regression (GWR), temporally weighted regression (TWR), and geographically and temporally weighted regression (GTWR) were applied to model the relationships between PM_2.5 and 5 air pollutants. Results: The LMM and all GWR-based models (i.e., GWR, TWR, and GTWR) showed great advantages over OLS in terms of higher model R² and more desirable model residuals, especially TWR and GTWR. The GWR, LMM, TWR, and GTWR improved the model explanation power by 3%, 5%, 12%, and 12%, respectively, from the R² (0.85) of OLS. TWR yielded slightly better model performance than GTWR and reduced the root mean squared errors (RMSE) and mean absolute error (MAE) of the model residuals by 67% compared with OLS; while GWR only reduced RMSE and MAE by 15% against OLS. LMM performed slightly better than GWR by accounting for both temporal autocorrelation between observations over time and spatial heterogeneity across the 13 cities under study, which provided an alternative for modeling PM_2.5. Conclusions: The traditional OLS and GWR are inadequate for describing the non-stationarity of PM_2.5. The temporal dependence was more important and significant than spatial heterogeneity in our data. Our study provided evidence of spatial–temporal heterogeneity and possible solutions for modeling the relationships between PM_2.5 and 5 criteria air pollutants for Heilongjiang province, China.

Water is an indispensable commodity for the survival of all living beings and for their well-being. The objective of this work is to evaluate the level of pollution of different drinking water sources consumed and its link with health in Pelengana commune, Mali. Samples of water were taken from various sources, namely, hand pumps, boreholes, dug wells, and shallow wells for physical, chemical, heavy metals, and bacteriological analyses, using American Public Health Association (APHA) Standard Techniques. Results revealed that the nitrate-nitrogen (NO₃⁻N) values of the water samples from the different water sources had concentrations exceeding the U.S. Environmental Protection Agency's (US-EPA) regulation of 10 mg/L, as well as World Health Organization Guideline for Drinking Water Quality (WHO GDWQ) (11 mg/L). The same applies to heavy metals such as Cd, Pb, and Fe, in which, concentrations exceed their allowable limits in certain locations. Moreover, apart from water samples from some different boreholes, total coliform, and Escherichia coli have been detected in all selected water sources, which indicates fecal contamination. In all, there is a pressing need to stop the consumption of drinking water from contaminated sources and to effect appropriate treatment.

Phosphorus (P) is the restraining aspect in the forest ecosystem, particularly in temperate regions, and makes the ecosystem more liable to nitrogen (N)-derived acidification. However, it remains poorly understood how N and P fertilization together affects soil-P availability and other soil properties. To address this question, a factorial experiment was conducted with N and P additions under two forest ecosystems, i.e., Korean pine plantation (KPP) and natural Korean pine forest (NKPF). Both forests were divided in to three subplots and each subplot underwent four different treatments, i.e., C: control (no N and P addition), L: Low treatment (5 g N m⁻² a⁻¹ + 5 g P m⁻² a⁻¹), M: Medium treatment (15 g N m⁻² a⁻¹ + 10 g P m⁻² a⁻¹), and H: High treatment (30 g N m⁻² a⁻¹ + 20 g P m⁻² a⁻¹). Results revealed that the soil-P fractions changed during N and P fertilization over time although organic-P (Po) fractions were lower than inorganic-P (Pi) fractions. The residual P was increased overall, along with N deposition in soil. Soil organic carbon (SOC) was more present in NKPF soils as compared to KPP. Principal component analysis (PCA) indicated that at medium treatment there is maximum availability of P fractions as compared to other treatments in both forests, while high treatment showed some fixation of P in soils across both forests. Furthermore, SOC showed a negative correlation with residual P, while pH showed a positive correlation. Total N in soil showed a negative correlation with soil pH and residual P. Therefore, it is recommended that application of N and P at the rate of 15 g N m⁻² a⁻¹ + 10 g P m⁻² a⁻¹ is suitable in these two forest types to enhance P availability.

Despite their small size, cryptogams (lichen, liverwort, and moss) are important for ecosystem stability. Due to their strong stress resistance, cryptogams often cover extreme environments uninhabitable for vascular plants, which has an important impact on the material cycle and energy flow of various terrestrial ecosystems. In this article, we review and discuss the effects of cryptogams on soil properties (moisture and fertility) and vascular plant regeneration over the past two decades. Cryptogams strongly affect soil water content by influencing precipitation infiltration, non-rainfall water input, soil evaporation, soil water holding capacity, and soil permeability, ultimately helping to reduce soil water content in areas with low annual precipitation (600 mm) or where the soil has other water sources, the presence of cryptograms is conducive to soil water accumulation. Cryptogam plants can increase soil fertility and the availability of soil nutrients (TOC, TN, TP, TK, and micronutrients) in harsh environments, but their effects in mild environments have not been sufficiently investigated. Cryptogam plants exert complex effects on vascular plant regeneration in different environments. The primary influence pathways include the physical barrier of seed distribution, shading, allelopathy, competition, influences on ectomycorrhizal development and individual reproduction, and the regulation of soil water content, temperature, and nutrients.

An assessment of consumer quality perception, as well as some physical and chemical characteristics of water samples sourced from wells, boreholes, and rivers in the locality of Pelengana commune, in Mali, was carried out. The World Health Organization (WHO) Guideline (or other) Values (GVs) for drinking water quality was used as a benchmark. One-way analysis of variance (ANOVA) alongside Duncan's multiple comparison tests for significant differences, and Principal Component Analysis (PCA) were used in analyzing differences and correlations regarding the parameters investigated. Results revealed that the majority of the households (61.2%) regarded wells and river water as unsafe for drinking. The physical and chemical quality of water was affected by climatic season. Also, with the exception of iron (average values), the parameters studied met the WHO GVs. Based on the analyzed parameters, the quality of these different water sources is chemically acceptable.

Coarse wood debris (CWD) plays a critical role in forest productivity, nutrient cycling, decomposition, and carbon sequestration, and shapes the carbon pool in the forest ecosystem. However, the elemental composition of CWD varies among different forest types and decay classes for the same dominant tree species (Pinus koraiensis, PK). We compared CWD elemental composition across different forest types (Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF), Betula costata-Pinus koraiensis forest (BPF), Tilia amurensis-Pinus koraiensis forest (TPF)), considering four classes of wood decay. Results showed that N, P, Mg, Mn, Na, Zn, S, Al, and Fe concentrations almost totally increased with decay level for all three forest types, except for K in all three forest types and B in Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF). Similarly, maximum concentrations of N, P, B, Mg, K, C, Zn, and Mn of CWD were observed in Betula costata-Pinus koraiensis forest (BPF) under varying decay classes, but their maximum concentrations of Fe and S were found in Picea koraiensis-Abies nephrolepis-Pinus koraiensis forest (PAPF) and Tilia amurensis-Pinus koraiensis forest(TPF), respectively. Only C content did not significantly differ in decay classes across all three forest types. The C:N ratio decreased significantly with increasing decay levels across all forest types. The decay rates were significantly related to N concentration and C:N ratio in decay classes across all forest types. These results suggest that C and N concentration are the key factors affecting its decomposition. The variation in nutrient concentrations observed here underscores the complexity of nutrients stored in wood debris in forested ecosystems.