Air pollution is a serious threat to ancient sites and cultural relicts. In this study, we collected indoor and outdoor PM₂.₅ samples and individual particles at the Exhibition Hall of Jinsha Site Museum in June 2020, and then the chemical components, sources, morphology, and mixing state of the fine particulate matter were analyzed. Our results show that the indoor and outdoor PM₂.₅ concentrations at the Exhibition Hall were 33.3±6.6 and 39.4±11.4 μg m⁻³, respectively. Although the indoor and outdoor concentrations of OC and EC were close, the proportion of secondary organic carbon in OC outdoor (33%) was higher than that indoor (27%). The PM₂.₅ was alkaline both indoors and outdoors, and the outdoor alkalinity was stronger than the indoor alkalinity. SNA (SO₄²⁻, NO₃⁻, and NH₄⁺) was the dominant component in the water-soluble inorganic ions; Na⁺, Mg²⁺, and Ca²⁺ were well correlated (R²> 0.9), and Cl⁻ and K⁺ were also highly correlated (R²> 0.8). Enrichment factor analysis showed that Cu (indoor) and Cd were the main anthropogenic elements and that Cd was heavily enriched. Principal components analysis showed that the main sources of PM₂.₅ at Jinsha Site Museum were motor vehicles, dust, secondary sources, and combustion sources. The individual particles were classified as organic matter, S-rich, soot, mineral, and fly ash/metal particles, and most of these particles were internally mixed with each other. At last, we proposed pollution control measures to improve the air quality of museums and the preservation of cultural relicts.

Aluminum phosphide (ALP) poisoning is a true medical emergency associated with high mortality. The lack of a specific antidote for ALP poisoning mandates searching for new treatment modalities. This study aimed to evaluate the effectiveness and safety of gastric decontamination by paraffin oil in cases with acute ALP poisoning. This study was a randomized, controlled, parallel-group, single-blind, phase II clinical trial conducted over a period of 6 months. Sixty-two patients with acute ALP poisoning were randomly allocated into two equivalent groups. In both groups, the standard ALP treatment was given. Gastric decontamination in the control group was performed by saline and sodium bicarbonate 8.4%, while in the intervention group, it was done by paraffin oil and sodium bicarbonate 8.4%. All patients were subjected to history taking, clinical examination, and laboratory investigations. The outcomes were evaluated. The median age of the studied patients was 20 years. Most of the studied cases were females, single, and from rural areas. The median delay time was 1 h. All patients included in the study alleged ingestion of ALP during suicidal attempts. Twelve hours after admission, many clinical and laboratory findings were significantly better in the intervention group. The need for intubation, mechanical ventilation, and total amount of vasopressors was significantly lower, and the mortality rate was non-significantly lower in the intervention group compared to the control. The median length of hospital stay was significantly shorter in the control group. Gastric decontamination with paraffin oil and sodium bicarbonate 8.4% could be valuable in reducing ALP poisoning severity, the need for intubation, mechanical ventilation, and vasopressors.

The present work focused on the utilization of three local wastes, i.e., rambutan (Nephelium lappaceum), langsat (Lansium parasiticum), and mango (Mangifera indica) wastes, as organic substrates in a benthic microbial fuel cell (BMFC) to reduce the cadmium and lead concentrations from synthetic water. Out of the three wastes, the mango waste promoted a maximum current density (87.71 mA/m²) along with 78% and 80% removal efficiencies for Cd²⁺ and Pb²⁺, respectively. The bacterial identification proved that Klebsiella pneumoniae, Enterobacter, and Citrobacter were responsible for metal removal and energy generation. In the present work, the BMFC mechanism, current challenges, and future recommendations are also enclosed.

Understanding the dynamics of water quality in any water body is vital for the sustainability of our water resources. Thus, investigating spatio-temporal changes of dominant water quality parameters (WQPs) in any study is indeed critical for proposing the appropriate treatment for the water bodies. Traditionally, concentrations of WQPs have been measured through intensive fieldwork. Additionally, many studies have attempted to retrieve concentrations of WQPs from satellite images using regression-based methods. However, the relationship between WQPs and satellite data is complex to be modeled accurately by using simple regression-based methods. Our study attempts to develop a machine learning model for mapping the concentrations of dominant optical and non-optical WQPs such as electrical conductivity (EC), pH, temperature (Temp), total dissolved solids (TDS), silicon dioxide (SiO₂), and dissolved oxygen (DO). In this context, a remote sensing framework based on the extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP) regressor with optimized hyper parameters (HPs) to quantify concentrations of different WQPs from the Landsat-8 satellite imagery is developed. We evaluated six years of satellite data stretching spatially from upstream to downstream Ankinghat to Chopan (20 stations under Central Water Commission (CWC), Middle Ganga Basin) for characterizing the trends of dominant physico-chemical WQPs across the four clusters identified in our previous study. Through the developed XGBoost and MLP regression models between measured WQPs and the reflectance of the pixels corresponding to the sampling stations, a significant coefficient of determination (R²) in the range of 0.88–0.98 for XGBoost and 0.72–0.97 for MLP were generated, with bands B1–B4 and their ratios more consistent. Indeed, these findings indicate that from a small number of in-situ measurements, we can develop reliable models to estimate the spatio-temporal variations of physico-chemical and biological WQPs. Therefore, models generated from Landsat-8 could facilitate the environmental, economic, and social management of any waterbody.

The ecological footprint attempts to quantify human impact on nature and its resources necessary to satisfy human needs. This research study explores the long-run implications of fiscal policy on the ecological footprint in Pakistan empirically, keeping different socio-economic factors into consideration. Per annum, time series data have been collected between 1976 and 2018, and the ARDL model is applied to investigate this long-run and short-run association. The conclusion of ARDL model shows that a 1% increase in public development expenditures, total population, GDP, and energy consumption increase 0.19, 2.17, 1.16, and 2.17% ecological footprint, respectively, in Pakistan between 1976 and 2018 vice versa. However, it is also derived that a 1% increase in public tax and non-tax revenue and current public expenditures (in health, education, and other social sectors) shrink 0.36 and 0.013% ecological footprint in the long run in Pakistan. For policy implications, these results focus on practical fiscal policy significance to achieve environmental targets in Pakistan, suggesting an increase in public current expenditures in public and social sectors and increasing public revenue by expanding the tax base, which will ultimately reduce ecological footprint in the long run in Pakistan.

This study measures the energy rebound effects of Chinese energy and coal power use in Chinese energy-intensive industries by using latent class stochastic frontier models like LMDI, and other various econometric estimation approach for coal-supplying regions in China ranging between 1992 and 2018. The findings reveals that China’s coal sector’s average capacity consumption is 0.81%, with a pattern of first increasing and then decreasing, falling to 0.68% in 2016 specifically. The coal capacity operation rate concerning low as well as depleted regions is generally strong, with limited space for expansion. In 2015 and 2016, the utilization rate of coal production potential in moderate-producing areas fell about 42%. Economic development variables affect the capacity utilization levels of moderate, weak, and depleted generating regions. At the same time, the price volatility cannot induce a practical improvement in the ability utilization rate, which means that China’s coal industry is mainly un-marketized. China’s energy efficiency increased about 19.98% among 2000 and 2016, while the rapidest expansion pattern has been noted in the eastern province at 39.86%, next to central (11.71%) and western regions (9.59%). The take back impact via the renewable energy and renewable productivity channels is estimated as 12.34% and 25.40%, respectively. Therefore, the take back impact is of significant importance regarding energy preservation, as China’s cumulative renewable energy use is equal to China’s aggregate energy use. On such findings, recent research also contributed by presenting novel policy implications for key stakeholders.

In this paper, one kind of acid–alkali modified sludge-based biochar (ASBC) was synthesized, characterized, and employed as adsorbent for the removal of pefloxacin. The characterization results showed that the specific surface area (SSA) of ASBC (53.381 m²/g) was significantly higher than that of SBC (24.411 m²/g). ASBC had a rougher surface, larger particle distribution, lower zero point charge, and richer functional groups (e.g., C-O and O–H) than SBC. The adsorption capacity of ASBC was 1.82 times than that of SBC. After 8 adsorption cycles in reuse experiment, the adsorption capacity of ASBC for pefloxacin still reached 144.08 mg/L, indicating that ASBC has good reusability. Static experiments showed that the optimal pH value was 6.0 in the adsorption of pefloxacin on SBC and ASBC. The result of adsorption kinetics indicated that the pseudo-second-order model could describe well the adsorption process. The Freundlich model was better than the Langmuir model to describe the adsorption of pefloxacin by ASBC, indicating that the adsorption process was mainly multilayer adsorption. Thermodynamic result showed that the adsorption of pefloxacin by ASBC was spontaneous and endothermic. The removal mechanism of pefloxacin by ASBC is mainly the substitution reaction and π-π EDA interaction. In summary, acid–alkali modified biochar is an effective adsorbent for pefloxacin in aqueous solution, and has great application prospects.

Central environmental inspection (CEI) is an environmental governance tool launched by the Chinese central government in recent years. The aim of CEI is to enhance the implementation of environmental regulations by going beyond supervising enterprises to supervise local governments. Previous studies have shown that CEI is beneficial for improving corporate environmental performance, but the relationship between CEI and the environmental behavior of companies achieving a high level of environmental performance is not clear. Drawing on principal-agent theory, this study explains how CEI influences corporate green innovation by changing the incentive structures of local governments and firms for adopting different environmental strategies. Moreover, two boundary conditions between CEI and corporate green innovation are identified: political connections and industry competition. The boundary conditions affect the individual and collective bargaining intentions of companies to comply with environmental regulations. We test our hypotheses by using a sample of 1152 publicly traded industrial firms in China from 2014 to 2018. Our findings show that CEI is conducive to corporate green innovation. This positive effect is strengthened in politically connected firms or firms in highly monopolized industries with lower bargaining intentions. Our study contributes to a better understanding of the effect of CEI on micro (firm-level) environmental behaviors and the antecedents of corporate green innovation.

The agriculture sector creates nearly a quarter of the total GHG emissions globally as production and transportation activities in the agriculture sector mostly use fossil fuels, creating carbon emissions. In this regard, it is highly important to study the environmental sustainability of agriculture sector growth by using the theory of environmental Kuznets curve (EKC). Furthermore, this research study is aimed to assess the moderation role of transportation competitiveness in determining the carbon emissions of transportation sector by using agriculture sector value addition. The study uses panel quantile regression technique for data analysis of 121 countries by covering time period from 2008 to 2018. The study results validated the agricultural EKC across four different quantile groups based on carbon emissions of transport sector. The moderation of transportation competitiveness is observed in changing the turning point and flattening of agricultural EKC indicating the early achievement of maturity. The quality of institutions and planned increase of population can help reduce carbon emissions of transportation sector. The moderation of transportation competitiveness implicates the importance of planning and efficiently operating the transportation sector to mitigate carbon emissions.

The objective of this study is to investigate the correlation between atmospheric pollen concentration and daily visits for allergic conjunctivitis. Daily counts of outpatient visits for allergic conjunctivitis, atmospheric pollen concentration, and meteorological data during pollen season of 2018 and 2019 were collected from Beijing Shijitan Hospital, China. A time-series analysis on generalized additive model with Poisson distribution was used to estimate the relationship between pollen concentration and visits for allergic conjunctivitis, after controlling for the time trend, weather variables, day of the week, and holiday effect. The RStudio was used to generate Spearman correlation coefficients and then to plot the lag-response curves for specific and incremental cumulative effects of relative risk (RR). There was a moderate positive correlation between pollen concentration and visits for allergic conjunctivitis, and Spearman’s correlation coefficient was 0.521 in 2018 and 0.515 in 2019 (P<0.01). The specific cumulative effect peak associated with per 10 grains/kmm² increases of atmospheric pollen concentration was within 0 day, and the lag time was 8 days(2018, 2019). The incremental cumulative effect peak associated with per 10 grains/kmm² increases of atmospheric pollen concentration occurred on lag day 10 (2018) and lag day 8 (2019), and the lag time was 14 days (2018) and 20 days (2019). Elevated concentrations of pollen increase the risk of allergic conjunctivitis with a time lag effect.