Background and aims: Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data.Design: Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017.Setting and Participants: Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries.Measurements: Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ⁹‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ⁹‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads.Findings: Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge.Conclusions: The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data.

This is the first study of broad range of chemical classes CECs conducted in the upper Wisla river catchment including the biggest WWTPs in this region and surface waters. The list of compounds is extensive and the paper provides, for the first time, better understanding of environmental burden from PCPCs in Poland. Cumulative contribution of hypertension pharmaceuticals, nonsteroidal anti-inflammatory drugs (NSAIDs) and lifestyle chemicals was 89% and 95% in wastewater influent, and 75% in wastewater effluent at both WWTPs. Significant removal efficiencies, exceeding 90%, were found for parabens, UV filters, NSAIDs, steroid estrogens, plasticizers, antibacterials/antibiotics, stimulants and metabolites and lifestyle chemicals. The comparison of the average mass loads of CECs between the influent and effluent, has shown that 27% and 29% of all detected CECs were removed by less than 50%. An increase of concentrations of CECs in the effluent was observed for 18% and 20% of all detected CECs in Kujawy and Plaszow WWTPs, respectively. Negative mass balances of fexofenadine, venlafaxine, o-desmethyltramadol, ketamine and temazepam were noted within WWTPs, which are a result of dissolution of persistent contaminants accumulated in aggregates and/or back-transformation or de-conjugation of metabolites into parent compounds. 44 CECs were detected in surface waters located upstream and downstream of the WWTPs. The concentrations of compounds were largely dependent on the dilution factor of WWTP discharge. The risk quotation (RQ) values for compounds present in surface waters were calculated in relation to their potential for bioaccumulation. Among compounds with high potential for bioaccumulation, with log K_OW ≥ 4.5, diclofenac, atorvastatin and triclosan were found to be of high risk. Many CECs with high, moderate or even low environmental impact have shown high potential for bioaccumulation and should be considered as priority at the same risk level. Moreover, possible synergistic action is still of concern.

Solid particles impair the performance of the photovoltaic (PV) modules. This results in power losses which lower the efficiency of the system as well as the increases of temperature which additionally decreases the performance and lifetime. The deposited dust chemical composition, concentration and formation of a dust layer on the PV surface differ significantly in reference to time and location. In this study, an evaluation of dust deposition on the PV front cover glass during the non-heating season in one of the most polluted European cities, Kraków, was performed. The time-dependent particle deposition and its correlation to the air pollution with particulate matter were analysed. Dust deposited on several identical PV modules during variable exposure periods (from 1 day up to 1 week) and the samples of total suspended particles (TSP) on quartz fibre filters using a low volume sampler were collected during the non-heating season in the period of 5 weeks. The concentration of TSP in the study period ranged between 12.5 and 60.05 μg m⁻³ while the concentration of PM10 observed in the Voivodeship Inspectorate of Environmental Protection traffic station, located 1.2 km from the TSP sampler, ranged from 14 to 47 μg m⁻³. It was revealed that dust deposition density on a PV surface ranged from 7.5 to 42.1 mg m⁻² for exposure periods of 1 day while the measured weekly dust deposition densities ranged from 25.8 to 277.0 mg m⁻². The precipitation volume and its intensity as well as humidity significantly influence the deposited dust. The rate of dust accumulation reaches approximately 40 mg m⁻²day⁻¹ in the no-precipitation period and it was at least two times higher than fluxes calculated on the basis of PM10 and TSP concentrations which suggest that additional forces such as electrostatic forces significantly influence dust deposition.

The maximisation of the efficiency of the photovoltaic system is crucial in order to increase the competitiveness of this technology. Unfortunately, several environmental factors in addition to many alterable and unalterable factors can significantly influence the performance of the PV system. Some of the environmental factors that depend on the site have to do with dust, soiling and pollutants. In this study conducted in the city centre of Kraków, Poland, characterised by high pollution and low wind speed, the focus is on the evaluation of the degradation of efficiency of polycrystalline photovoltaic modules due to natural dust deposition. The experimental results that were obtained demonstrated that deposited dust-related efficiency loss gradually increased with the mass and that it follows the exponential. The maximum dust deposition density observed for rainless exposure periods of 1 week exceeds 300 mg/m² and the results in efficiency loss were about 2.1%. It was observed that efficiency loss is not only mass-dependent but that it also depends on the dust properties. The small positive effect of the tiny dust layer which slightly increases in surface roughness on the module performance was also observed. The results that were obtained enable the development of a reliable model for the degradation of the efficiency of the PV module caused by dust deposition. The novelty consists in the model, which is easy to apply and which is dependent on the dust mass, for low and moderate naturally deposited dust concentration (up to 1 and 5 g/m² and representative for many geographical regions) and which is applicable to the majority of cases met in an urban and non-urban polluted area can be used to evaluate the dust deposition-related derating factor (efficiency loss), which is very much sought after by the system designers, and tools used for computer modelling and system malfunction detection.

The escalating crisis of environmental degradation, with waste fires acting as a potent accelerant, has reached a critical juncture that demands immediate attention. This crisis disproportionately affects developing and low-income nations, where unregulated disposal and incineration in open areas have become rampant. These open waste fires serve as hotbeds for many environmental hazards ranging from air and water pollution to soil degradation. In addition, they contribute to the growing threat of marine litter and are a significant source of greenhouse gas emissions, exacerbating global climate change. Beyond their environmental toll, waste fires present an immediate and long-term threat to human health, causing respiratory problems and skin conditions and potentially leading to more serious health outcomes, such as cancer. Their impacts are multidimensional, affecting not only the environment but also pose severe health risks to communities, especially those near waste-burning sites. In this technologically advanced era, the application of artificial intelligence (AI), Machine Learning (ML), and deep learning technologies has the potential to revolutionize waste fire management. These technologies can significantly improve the accuracy of identifying, monitoring, and ultimately mitigating waste fires, making them indispensable tools in the fight against this complex issue. This article offers a comprehensive and in-depth examination of the historical evolution of waste fires, with the aim of shedding light on the critical factors that contribute to their occurrence. We explore the scientific mechanisms by which waste fires lead to environmental pollution and public health crises, providing a holistic understanding of their far-reaching impacts. We present an overview of significant research initiatives, policy interventions, and technological solutions that have been proposed or implemented by authoritative bodies around the world. By synthesizing existing research and offering new insights, this paper aims to facilitate a deeper understanding of the intricacies of waste fires and spur innovative solutions for their sustainable management and eventual eradication. Therefore, this article focuses on environmental and human health problems while outlining the comprehensive approach and potential contributions to solving this critical issue.