This research investigated the current methods of characterization of ions and metals in particulate matter pollutants from different emission sources. The study was conducted through the Proknow-C methodology, in which a portfolio that includes scientific and review articles was selected. The document addresses different methodologies currently used to quantify diverse ions and metals (IIMM) found in particulate matter (PM), specifically focused on PM₁₀ and PM_2.5. The investigation was made going through the types of filters used to capture the pollutant, the equipment and the corresponding characterization techniques. Results show the Proknow-C method is a reliable way to analyze PM pollution research, revealing the state of art for metals and ions types, characterization technologies, current situations and trends. Sulfate, nitrate, and ammonium ions are found in concentrations between 70 and 80% of the PM. Among the main metals found are chromium, nickel, lead, cadmium, iron, manganese, coper, and zinc. The main detection method found in the studied research was inductively coupled plasma mass spectrometry. It was also found that geographic information systems are a good tool for integrating special data with PM and air pollution, which could accelerate the diagnosis and thus the actions to give solution to the problem.

As set out in the Sustainable Development Goals, it is necessary to achieve universal and equitable access to safe drinking water services for all the world’s population. Appropriate water treatment alternatives for rural areas should be prioritised to achieve this goal. In this work, a simplified drinking water treatment system (SDWTS), which has great potential for application in small communities and rural areas, was evaluated on a pilot scale for turbidity and apparent colour removal using synthetic raw water. The SDWTS integrates Upflow Gravel Filter in Layers (UGFL) and Rapid Sand Filter (RSF) with previous coagulation. This evaluation was carried out using a 2${}^3$ factorial experiment, with the factors: type of water, type of coagulant and flow. The factorial design showed that the SDWTS had the highest turbidity removal efficiencies (>98.7%) with type II (20 NTU) water and PACl coagulant, while flow rate had no significant effect on turbidity removal. Under optimal operating conditions (type II water, PACl and 1.0 m${}^3$/d), the SDWTS produces treated water that meets the standards required by Colombian regulations and World Health Organisation recommendations for drinking water, concerning the variables: turbidity, apparent colour, total coliforms, $E.$ $coli$, pH, electrical conductivity and Al. The SDWTS maintained its capacity to produce potable water when evaluated with the increased operating flow (up to 3.0 m${}^3$/d) and raw water turbidity (up to 50 NTU). The SDWTS can be an efficient and innovative alternative for water treatment, and its implementation in small communities can contribute to equitable access to drinking water.

The carbonaceous particles represent a significant fraction in the particulate matter (PM) and are considered an environmental hazard due to their effects on climate and health. The main goal in this research is to identify and analyze the scope that have been achieved so far on the characterization and measurement of the carbonaceous fraction present in PM, a great contribution to global pollution and thus to the deterioration of public health. The ProKnow-C methodology was used to build a bibliographic portfolio and perform a bibliometric and systemic analysis of the information found in the chosen databases. The contribution of these carbonaceous compounds to PM is very significant, reaching values up to 50%. The most used methods for the determination of organic and elemental carbon are thermo-optical reflectance and transmittance. Positive Factorization models are used worldwide to determine potential sources of particulate matter emissions. Even though various studies have been developed to understand these carbonaceous substances, there are several limitations in the measurements and limited knowledge on the subject. The positive outcomes and future possibilities were analyzed as well.

Particulate matter (PM), particle pollution that can travel long distances, is a big concern because it contains liquid droplets or microscopic solids resulting in significant health issues such as respirational and cancer problems. Therefore, the characterization of these particles is very significant as a hazard to public health. PM can be identified by X-ray diffraction (XRD) and Raman spectroscopy (RS), both powerful and non-destructive technologies. RS, in particular, allows the identification of black carbon, considered one of the pollutants with the greatest influence on climate change. Another important technology for the evaluation of inorganic and organic functional groups present in PM compounds is the Fourier transform infrared spectroscopy (FTIR). X-ray fluorescence (XRF) provides elemental analysis, revealing, in many cases, the original source of the sample. In order to understand the current state of the art, the Proknow-C method was applied to track the most recent information on PM characterization. Aspects such as sample collection, filter material, characterization parameters, PM components, and the advantages and limitations of each technique are discussed. PM minerals are found to be composed of silicates, oxides, sulfates, and carbonates. The elemental components of PM are classified into five categories: marine aerosol, mineral material, anthropogenic elements, organic carbon, and elemental carbon. The XRD technique is a powerful, fast, and non-destructive tool to identify various minerals present in PM. On the other hand, the XRF technique requires minimal sample treatment, but its sensitivity is limited for the determination of trace metals and some relevant environmental elements. FTIR spectroscopy is able to identify and quantify all organic functional groups present in atmospheric PM. Despite its advantages, a proper choice of calibration method is crucial to ensure its effectiveness. RS is fast and simple, although it only detects Raman-active functional groups. These are some of the advantages and limitations of these techniques addressed in the following review article.