Ammonia (NH₃) is a toxic, environmental pollutant, and irritant gas. Previous studies reported the toxic effects of NH₃ which led to inflammation in various organs of chicken. However, the exact mechanism of NH₃-induced inflammation in chicken lymphoid organs bursa of fabricius (BF) and thymus is still elusive. Thus, this study was designed to investigate NH₃-induced inflammation in chicken BF and thymus. Experimental chickens were divided into low (5.0 mg/m³), middle (10.0–15.0 mg/m³), and high (20.0–45.0 mg/m³) NH₃-treated groups. To investigate NH₃-induced inflammation in chicken’s BF and thymus, histological observation, NO content and iNOS activity, inflammatory cytokine contents, and mRNA levels were performed by light microscopy, microplate spectrophotometer, ELISA assay, and qRT-PCR. The finding of the present study showed that NH₃ exposure reduced BF and thymus index, increased nitric oxide (NO) content and inducible nitric oxide synthase (iNOS) activity, inflammatory cytokine contents and mRNA levels of nuclear factor-kappa B (NF-κB), cyclooxygenase-2 (Cox-2), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), IL-10, IL-1β, IL-18, toll-like receptor 2A (TLR-2A), and iNOS. Histopathological examination revealed signs of inflammation including increased nuclear debris and vacuoles in the cortex and medulla of thymus and bursal follicles. Conclusively, our findings displayed that NH₃ exposure affects the normal function of BF and thymus and led inflammation. The data provided a new ground for NH₃-induced toxicity and risk assessment in chicken production.

Until now, a number of epidemiological studies have focused on the association between ambient particulate matter pollution and chronic obstructive pulmonary disease (COPD), especially in developed countries. There are limited evidences on the association between short-term exposure to particulate matters (PM₂.₅, PMC, and PM₁₀) and overall hospital outpatient visits for COPD at the same time in China. Thus, a time-series analysis on the short-term association between three subtypes of PM (PM₂.₅, PMC, and PM₁₀) and daily hospital outpatients for COPD in Lanzhou, China was conducted, from 2014 to 2017.An over dispersed, generalized additive model was used to analyze the associations after controlling for time trend, weather conditions, day of the week, and holidays. Stratified analyses were also performed by age and gender. The results disclosed that a 10-μg/m³ increase in PM₂.₅ concentration at a lag of 0–7 days was associated with 1.190% (95% CI 0.176~2.215%). For PMc, therewere not statistically significant effects at any lag days, but we could find the greatest effect at lag07 that a 10-μg/m³ increase in concentration was associated with 0.014% (95% CI − 0.065~0.093%). PM₁₀ also exerted a high effect for COPD (0.185% increase; 95% CI − 0.046~0.417%) when 6 days of exposures (lag6), however, no significance relationship could be found. For COPD among males, positive results were observed for PM₂.₅ with lags of 0–7 days, a 10-μg/m³ increase was 1.184% (95% CI 0.095~2.284%). The effect of PM₂.₅ on females was also most significant at lag07, a 10-μg/m³ increase was 1.254% (95% CI 0.053~2.469%). For those aged < 65 years old, PM₂.₅ was not statistically significant at all lag days, but it reached the maximum at lag07, a 10-μg/m³ increase was 0.978% (95% CI − 0.139~2.108%). For those aged 65 ≥ years old and older, PM₂.₅ had a statistically significant lag effect at lag1, lag2, lag3, lag02, lag03, lag04, lag05, lag06, and lag07, and it was most significant at lag07; a 10-μg/m³ increase was 1.906% (95% CI 0.553~3.277%). Short-term exposure to PM₂.₅ was associated with increased risk of hospital visits for COPD. In particular, the elderly (aged ≥ 65 years old) and males were relatively more sensitive to PM₂.₅, and were affected right away after the PM₂.₅ concentration went up.

The serious ambient fine particulate matter (PM₂.₅) is one of the key risk factors for lung cancer. However, existing studies on the health effects of PM₂.₅ in China were less considered the regional transport of PM₂.₅ concentration. In this study, we aim to explore the association between lung cancer and PM₂.₅ and then forecast the PM2.5-induced lung cancer morbidity and mortality in China. Ridge regression (RR), partial least squares regression (PLSR), model tree-based (MT) regression, regression tree (RT) approach, and the combined forecasting model (CFM) were alternative forecasting models. The result of the Pearson correlation analysis showed that both local and regional scale PM₂.₅ concentration had a significant association with lung cancer mortality and morbidity and compared with the local lag and regional lag exposure to ambient PM₂.₅; the regional lag effect (0.172~0.235 for mortality; 0.146~0.249 for morbidity) was not stronger than the local lag PM₂.₅ exposure (0.249~0.294 for mortality; 0.215~0.301 for morbidity). The overall forecasting lung cancer morbidity and mortality were 47.63, 47.86, 39.38, and 39.76 per 100,000 population. The spatial distributions of lung cancer morbidity and mortality share a similar spatial pattern in 2015 and 2016, with high lung cancer morbidity and mortality areas mainly located in the central to east coast areas in China. The stakeholders would like to implement a cross-regional PM₂.₅ control strategy for the areas characterized as a high risk of lung cancer.

The formation of highly graphitic phenolic resin chars (GPFCs) during catalytic carbonization at relatively low reaction temperature (1200–1600 °C) using novel Ni-Zn-B alloy catalyst with small amount of addition (5–15%) was systematically studied. Only two kinds of graphites (turbostratic graphite and ordered graphite) can be found in GPFCs after catalytic carbonization with Ni-Zn-B and their proportions were changed with reaction conditions. When Ni-Zn-B was involved at 1200–1600 °C, the phenolic resin char was fully transformed to be graphite, and ordered graphite content increased to 28.42% at 1400 °C, which was also almost twice of ordered graphite content in the char catalyzed by pure Ni. But the order graphite content would decrease due to sintering at higher reaction temperature. The addition of Zn and B can promote nickel-based alloy catalytic action by reducing melt point and accelerating graphitization respectively. It was also found that ordered graphite content could be used as a key evaluation parameter to directly reflect the quality of GPFCs based on detailed characteristics analysis. The model between three reaction conditions (reaction temperature, retention time, catalyst content) and ordered graphite content was built with artificial neural network (ANN), and the prediction accuracy of ANN was high up to 91.48%.

The presence of plastic debris < 5 mm called microplastics (MPs) which results mainly from macroplastic’s fragmentation has been reported in aquatic ecosystems. Several studies have shown that MPs are persistent and their accumulation was observed in various aquatic species. However, the majority of studies focused on marine species, and much less on continental and estuarine biota. The goal of the present study was to investigate the effects of a mixture of two types of MPs (polyethylene and polypropylene), frequently found in natural environments, towards the ragworm Hediste diversicolor to determine their accumulation in organisms exposed through the water phase or sediment. Two concentrations of exposure were selected for medium and heavily contaminated areas reported for water phase (10 and 100 μg/L) and sediment (10 and 50 mg of MPs/kg). To study the potential toxic effect of MPs, immune parameters were selected since they are involved in many defense mechanisms against xenobiotics or infectious agents. An average number of MP items/worm ranging from 0 to 2.5 and from 1 to 36 were identified in animals exposed to the lowest and the highest concentration of MPs through water exposure. In worms exposed through sediment, less than 1 MP/worm was found and a greater number of particles were identified in depurated sediment. For immunotoxic impact, MP exposure induced a decrease in coelomocytes viability, but no alteration of phagocytosis activity, phenoloxydase, and acid phosphatase was measured. This study brings new results on the potential accumulation and immunotoxicity of MPs for the ragworm H. diversicolor who plays a key role in the structure and functioning of estuarine ecosystem.

The materials and byproducts of the processes used in the metal finishing industry are released as particle contaminants into the air in the workplace. The present study aimed to determine the concentrations and size distributions of these particles and of elements chromium, nickel, copper, manganese, cobalt, and lead (Cr, Ni, Cu, Mn, Co, and Pb, respectively) in a metal finishing industry and evaluate their potential health risks. Particles that are airborne from the dipping baths in the plant were sampled using a Sioutas cascade impactor at five different size fractions (PM>₂.₅, PM₁.₀–₂.₅, PM₀.₅–₁.₀, PM₀.₂₅–₀.₅, PM<₀.₂₅) and gravimetric analyses were conducted on the sampled filters. The GF-AAS 600 graphite atomic absorption spectrophotometer (PerkinElmer Corporation, Waltham, MA, USA) was used to analyze the elements and the method of USEPA was used to assess the health risk. The ratio of fine particles (PM₂.₅) to total suspended particles (TSPs) was 0.6. We observed that 50% of TSPs were composed of PM₁.₀ and that 68–88% of the metals were found in the fine particle fractions. Pb, Cr, and Mn were significantly positively correlated in the PM₁.₀ fraction, and the highest linear relationship was found between Pb and Cr (r = 0.85, p < 0.01). The total hazard quotient (HQ) for PM₂.₅ was 1.43, which is higher than the acceptable limit of 1.0. The excess lifetime cancer risk (ELCR) for hexavalent chromium (Cr[VI]) in PM₂.₅ was 6.09 × 10⁻⁵ for female workers and 6.54 × 10⁻⁵ for male workers, which are higher than the acceptable limit of 1.0 × 10⁻⁶, while total ELCRs for female and male workers were 6.21 × 10⁻⁵ and 6.21 × 10⁻⁵, respectively. The lifetime cancer risk associated with Cr(VI) in Cr electroplating plants should be taken into consideration as a significant health risk for the workers.

Metal pollution has been a serious problem facing river systems worldwide, which can adversely affect human health through food chain. The goal of this study was to determine the distribution, sources, and health risk of dissolved metals (Cr, Mn, Ni, Cu, Zn, As, Cd, Pb, Al, Sb, V, Co, Mo) in major rivers located in the hilly area of southeastern China (namely, Jiulongjiang River (JL), Minjiang River (MJ), Oujiang River (OJ), Qiantangjiang River (QT), Raohe River (RR), Fuhe River (FR), Xinjiang River (XR), Ganjiang River (GR), Xiushui River (XS), Xiangjiang River (XJ), Zishui River (ZR), Yuanjiang River (YR), Lishui River (LR)) during dry and wet seasons. Results indicated that metal concentrations were spatially and temporally distinct. Metals of Mn, Ni, Cu, Cd, Sb were significantly higher in specific rivers than other metals. And metals of Cr, Ni, As, and Al concentrations were obviously higher in dry season than in wet season. The comparison with drinking water guidelines of China and other countries indicated that waterbodies were polluted higher by Al than other metals at most sites. Metals in JL and XJ may have health risk to local adults with hazard index (HI) > 1. While special attention should be paid to As, which had a potential carcinogenic risk to adults in study area with CR higher than the critical value. Source analysis with statistical method indicated that point and non-point pollutants from anthropogenic activities are the main sources of metals, with the exception of Al, Ni, V, Cr, and Mo that were mainly from natural processes. This study could be useful for the management and protection of the China’s Southern hilly area river systems.

This study sets out to propose a new ensemble of probabilistic spatial modeling and multi-criteria decision-making comprised of stepwise areal constraining and Mahalanobis distance algorithms in order to assess areal suitability for landfilling. The Ardak watershed was selected as the study area due to encountering several cases of open garbage dumps and uncontrolled landfills which are one of the main sources of river water pollution in the upstream of the Ardak dam. The results revealed that the proposed algorithm successfully assists in inventory-irrespective probabilistic modeling of landfill siting which is mainly indebted to the role of areal constraining in providing training and validation samples for the Mahalanobis distance model. The latter also showed a robust pattern recognition results from which a discernible differentiation of the area was attained while the spatial dependencies between the environmental factors were taken into account. Mahalanobis distance also gave an outstanding performance in terms of goodness of fit (area under the success rate 89.367) and prediction power (area under the success rate 89.252). Based on a five-point scale classification scheme, about 2.7% and 2.6% of the study area, respectively, have high and very high suitability for landfilling, while the remaining area is shared between very low-to-moderate suitability classes. According to the current trail of literature regarding landfill site selection which mostly relies on mere areal filtering, a probabilistic model would give invaluable inferences regarding the pattern of suitability/susceptibility of the area of interest and causative role of the influential factors. Graphical Abstract