Carbon neutrality of tropical reservoirs is a big concern in recent years as some estimates project high methane emission from these reservoirs. While there are studies available on the impact of physical processes (stratification and mixing) on the biogeochemistry of tropical reservoirs, not much information is available on the inter-annual variability in the low-oxygen conditions and production/accumulation of hydrogen sulphide (H₂S) and methane (CH₄) during summer. This paper presents time series data based on monthly in situ observations from a tropical reservoir (Tillari, Maharashtra) situated in the Western Ghats in India. Sampling was carried out for temperature, dissolved oxygen (DO), H₂S, and CH₄ at a fixed location from March 2010 until June 2014. The reservoir experiences stable stratification during summer (March to June) with complete loss of oxygen and production of H₂S (max. ~ 9 μM) and CH₄ (max. ~ 185 μM) in the profundal zone. During the summer stratification, the hypolimnion acted as a pool of CH₄ with integrated values ranging between 3502 and 41,632 mg m⁻². However, the intensity and duration of anoxia varied during different years, influencing H₂S and CH₄ production. Mixing in the reservoir was observed between July and September in association with the monsoonal runoff, which increased the DO concentrations in the sub-surface layers. Besides, complete mixing was observed between December and February due to winter convection. This, however, was found to play an important role, as weaker mixing in the preceding year was associated with severe oxygen loss in the profundal zone during the following summer with a production of H₂S and CH₄. In contrast, more robust mixing during winter led to moderate low-oxygen conditions with less production of these gases in the subsequent summer. Based on our observations and considering a large number of reservoirs in the tropics, we hypothesise that with the present trends of global warming and less cold winters, low-oxygen conditions in the profundal zone may become more severe in the future with positive feedback on H₂S and CH₄ production during summer.

The emergence of COVID-19 and the spread of this novel disease around the world in 2020 has entailed several cultural changes; some of those changes are positive for the environment, such as the decrease in the concentration of atmospheric particulate matter. We compared the concentrations of PM₂.₅ and PM₁₀ recorded in October and November 2019 (pre-pandemic period) with the concentrations recorded from May to October 2020 (pandemic period) in the city of Arequipa, Peru. A significant decrease in the concentration of PM₂.₅ (less than 21.0%) and PM₁₀ (less than 21.5%) was observed on Sundays, when population movement was strongly restricted. First, we observed a significant correlation between PM₂.₅ and PM₁₀ concentration in the atmosphere and the number of infections reported in Arequipa, Peru. However, when we removed the data of Sundays from the database, these correlations were no longer significant. Subsequently, we correlated PM₂.₅ and PM₁₀ concentrations with the number of COVID-19 infections on the same day and up to a 20-day delay and found that from day 15 to day 18, PM₁₀ concentration was significantly correlated with COVID-19 infections, suggesting that SARS-CoV-2 might circulate attached to the coarse particle (PM₁₀) and that this fraction would act as infection vector. However, these results may reflect other factors, such as social or economic factors that could explain the dynamics of infection in Arequipa, Peru. Further research is needed to better understand the dynamics of the SARS-CoV-2 pandemic.

Based on the rebound model of particle–wall collision, the influence of adhesion force on the deposition process of particles on the smoke cake wall was studied by using atomic force microscopy (AFM) and automatic specific surface area (BET) and pore size distribution analyzer. The interaction between the deposition process and the spatial structure of smoke cake was analyzed. The results show that with the increase of diesel engine speed, Young’s modulus of particles decreases and the average particle size increases; the kinetic energy of particles impacting on the surface of smoke cake layer in diesel particle filter (DPF) increases; when the velocity of particles with the same particle size entering the wall increases, the maximum compression distance between particles and the surface of the smoke cake layer increases; and the adhesion force and adhesion energy increase. With the increase of diesel engine speed, the box counting dimension of smoke cake layer in DPF increases from 1.9478 to 1.996, the characteristic radius of pores decreases from 15.32 nm to 7.53 nm, the average pore diameter decreases, and the average pore volume increases. When the fractal dimension increases from 2.633 to 2.732, the deformation degree of particles increases, the smoke cake layer becomes more compact and dense, the internal structure of pores becomes more complex, the surface of pores is rougher, and particle adhesion requires overcoming larger adhesion barriers when particles adhere.

Cities are usually the final destination for consumable goods and services produced along supply chains and the most appropriate scale to implement policy. Consumption-based policies could complement current carbon emissions mitigation actions, but such studies at the city level are relatively rare. We used a demand-driven input-output model to explore a historical time series (1987–2012) of consumption-based emissions in Tianjin for the first time, a typical industrial city which has the largest carbon footprint in China. The results reveal the differences between consumption- and production-based emissions, and Tianjin has transformed from a producer city into a typical consumer city since 2000s, mainly due to infrastructure construction. There is more capital investment in industrial infrastructures than in real estate in Tianjin, causing the largest carbon footprint. The trade deficit and different carbon intensity have substantial influences on consumption-based emissions. Finally, population, income, and urbanization could enable a more accurate interpretation of urban carbon footprint growth. Demand-driven policy implications for addressing these emissions in booming industrial cities are discussed and provide a new perspective on carbon emissions mitigation. Our results offer valuable lessons on industrial cities’ strategies and initiatives for climate change mitigation worldwide, particularly in developing countries.

Due to the imbalance of technological level and industrial structure in regional economic development, the same carbon source can bring differentiated carbon emission levels in different regions, thus making the carbon emission show significant regional differences. In order to explore the regional differences in China’s provincial carbon emission intensity and the effect of relevant influencing factors, this paper combines EKC model and STIRPAT model to conduct research. Using carbon emission intensity and other influencing factors of China’s 30 provinces ranging from 2005 to 2017 to construct a panel data, the authors use exploratory spatial data analysis and Spatial Durbin Model to study the spatial effect of carbon emission intensity in China’s provincial regions and the impact of different development factors on carbon emission intensity. The results show that from 2005 to 2017, China’s carbon emission intensity gradually declined from east to west and from south to north. The inter-provincial carbon emission intensity of China presents an agglomeration effect in space, and the agglomeration effect gradually weakens with time. In addition, reducing energy intensity can reduce carbon emission intensity to a large extent. By optimizing industrial structure, increasing the degree of foreign trade and promoting financial development, carbon emission intensity can also be inhibited. Therefore, reducing the energy intensity of various industries and establishing inter-regional carbon emission cooperation mechanism will be effective to control the carbon emission intensity.

Fenton conditioning processes have been recently employed to improve the dewaterability of sewage sludge. However, it remains unclear whether the conditioning with Fenton’s reagent would simultaneously attenuate antibiotic resistance genes (ARGs) in sludge and improve sludge dewaterability. It was found in the present study that sludge pre-acidification played a pivotal role in simultaneously removing ARGs and improving sludge dewaterability by conditioning with Fenton’s reagent. When the sewage sludge was pre-acidified to pH = 3.0 and was then conditioned using Fenton’s reagent, the absolute abundances of the total ARGs and the total mobile genic elements (MGEs) in conditioned sludge were reduced by 1.85–2.10 and 2.84–3.12 log units, respectively. Additionally, sludge capillary suction time (CST) and specific resistance to filtration (SRF) were drastically reduced, and the moisture content (MC) in dewatered sludge cake was reduced to only 60.61–69.95%. Such effective attenuation of ARGs and MGEs in conditioned sludge led to their removal in both the dewatered sludge cakes and dewatering filtrate. However, only the improvement of sludge dewaterability was attained by sludge conditioning with Fenton’s reagent but without sludge pre-acidification. During the conditioning treatment, the removal of loosely bound extracellular polymeric substance (EPS) and tightly bound EPS in conditioned sludge contributed to the improvement of sludge dewaterability, and the damage of sludge microbial cells was highly correlated with the attenuation of antibiotic resistance. Thus, sludge pre-acidification combined with conditioning using Fenton’s reagent can be employed to simultaneously attenuate the antibiotic resistance in sewage sludge and improve sludge dewaterability.

Excessive Fe and Mn in groundwater of the Songnen Plain, northeast China, pose a threat to water security. Human activities over recent decades have had significant effects on the water quantity and quality of the Songnen Plain. By adopting the large city of Changchun in the Songnen Plain as a research area, this study analyzed the effects of the natural environment (including characteristics of soil and aquifer, climate, and groundwater level) and human activities (including groundwater salinization, groundwater exploitation, and nitrate effects) on groundwater Fe and Mn using statistical and spatial analysis methods. The results showed that the characteristics of soil and aquifer determine the source of groundwater Fe and Mn. The correlations between Fe and Mn with TDS (total dissolved solids) increased with increasing TDS from southeast to northwest in different microclimate regions. The salinization of groundwater caused by human activities will also lead to the increase of Fe content. The decrease in groundwater Fe and Mn was attributed to an increase in groundwater [Formula: see text], through the use of chemical fertilizers. The variation of Fe concentration in groundwater corresponded well with that of groundwater depth, but the excessive exploitation will lead to the continuous decrease in groundwater level and a corresponding decrease in the concentration of groundwater Fe. This study provides a reference for understanding the influence of human activities and the natural environment on groundwater hydrochemistry in the Songnen Plain.

In this work, zirconium chloride octahydrate/CTAB/vetiver grass-activated carbon (ZR/CTAB/VGAC) was prepared from vetiver grass-activated carbon (VGAC), using zirconium chloride octahydrate (ZR) and cetyltrimethylammonium bromide (CTAB) as modifiers. The optimized conditions of the simultaneous phosphate and nitrate removal by ZR/CTAB/VGAC were discussed, including amount of adsorbent, initial concentration, pH, contact time, and temperature. The simultaneous removal efficiency of phosphate and nitrate was 96.50% and 51.17% under optimized conditions. The structural and morphology of ZR/CTAB/VGAC was investigated by using automatic volumetric adsorption analyzer (BET), scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDAX), and Fourier transform infrared spectroscopy (FTIR). It was found that the removal efficiencies of phosphate and nitrate were enhanced dramatically because ZR and CTAB were introduced on the surface of VGAC after modification. Moreover, the adsorption data fitted significantly well with Freundlich isotherm model. It was described well by pseudo-second-order kinetic model. Phosphate and nitrate adsorbed via chemisorption (ion exchange) by ZR, CTAB, and functional groups of the surface of ZR/CTAB/VGAC. Electrostatic adsorption of AC in ZR/CTAB/VGAC also played an important role in the adsorption process. ZR/CTAB/VGAC is an excellent adsorbent, which could be applied to remove nitrate and phosphate from wastewater.

This work aims to assess multidimensional energy poverty and energy efficiency for environmental policy measures using data envelopment analysis (DEA), a DEA-Like mathematical composite indicator applied on a dataset based on multiple sets of variables from South Asian economies. The multidimensional energy poverty index (MEPI) is computed to analyze the combining effects and energy poverty in these countries. Simultaneously, South Asia’s metropolitan areas’ population rose by 130 million between 2001 and 2011 and is projected to expand by approximately 250 million by 2030. The findings reveal that endogenous increasing population shocks account for about 72% of energy use. In contrast, the long-term effects of remittance revenue, economic growth, and urbanization on energy use are approximately 20%, 8.25%, and 0.03%, respectively. This work advocates more coordinated and innovative policies to eliminate energy poverty. It can act as a base for policymakers and government officials to make efficient policies and enforce them properly in the regional power sector. Policies should be designed around a smarter use of biomass for cooking, alternate sources for domestic energy production, increased programs for biomass-based cookstoves, and periodic regional-level energy database development.