Ambient air quality is a complex issue that depends on multiple interacting factors related to emissions coming from energy production and use, transportation, industrial processes, agriculture, and waste and wastewater treatment sectors. It is also impacted by adverse meteorological conditions, pollutants concentrations, their transport and dispersion in the atmosphere, and topographic constraints. Therefore, air pollutants distribution is not uniform and their monitoring at proper temporal and spatial resolution is necessary. Drone-borne analytical instrumentation can fulfill these requirements. Thanks to the rapid development in the drone manufacturing sector as well as in the field of portable detectors construction, applications of unmanned aerial vehicles (UAVs) for atmospheric pollution monitoring are growing. The purpose of this work is to give an overview of this matter. Therefore, this paper contains basic information on UAVs (i.e., description of different types of drones with their advantages and disadvantages) and analytical instrumentation (i.e., low-cost gas sensors, multi-sensor systems, electronic noses, high-accuracy optical analyzers, optical particle counters, radiation detectors) used for the monitoring of airborne pollution. Different ways of payload integration are addressed and examples of commercially available solutions are given. Examples of applications of drone-borne analytical systems for pollution monitoring coming from natural (i.e., volcanoes, thawing permafrost, wildfires) and anthropological (i.e., urbanization and industrialization; extraction, transport and storage of fossil fuels; exploitation of radioactive materials; waste and wastewater treatment; agriculture) sources are also described. Finally, the current limitations and future perspectives are discussed. Although there is a great potential for drones applications in the field of atmospheric pollution monitoring, several limitations should be addressed in the coming years. Future research should focus on improving performances of available analytical instrumentation and solving problems related to insufficient payload capacity and limited flight time of commonly used drones. We predict that applications of drone-assisted measurements will grow in the following years, especially in the field of odor pollution monitoring.

To evaluate lung function responses to short-term indoor PM₁ and PM_2.5 concentrations, we conducted a panel study of healthy schoolchildren aged 13–14 years. The following lung function parameters FVC, FEV₁, PEF, and mid expiratory flows MEF₂₅, MEF₅₀, and MEF₇₅ were measured in 141 schoolchildren of the secondary school in Wroclaw, Poland in years 2009–2010. On days when spirometry tests were conducted, simultaneously, PM₁ and PM_2.5 samples were collected inside the school premises. Information about differentiating factors for children including smoking parents, sex, living close to busy streets, dust, mold, and pollen allergies were collected by means of questionnaires. To account for repeated measurements, the method of generalized estimating equations (GEE) was used. The GEE models for the entire group of children revealed the adverse effects (p < 0.05) of PM₁ and PM_2.5. Small differences in effects estimates per interquartile range (IQR) of PM₁ and PM_2.5 on MEF₂₅ (5.1 and 4.8 %), MEF₅₀ (3.7 and 3.9 %), MEF₇₅ (3.5 and 3.6 %) and FEV₁ (1.3 and 1.0 %) imply that PM₁ was likely the component of PM_2.5 that might have a principal health effect on these lung function parameters. However, the reduction of FVC and PEF per IQR for PM_2.5 (2.1 and 5.2 %, respectively) was higher than for PM₁ (1.0 and 4.4 %, respectively). Adjustment for potential confounders did not change the unadjusted analysis.

Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.