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.

Understanding the magnitude and distribution of the mixes of the near-ground carbon dioxide (CO₂) components spatially (related to the surface characteristics) and temporally (over seasonal timescales) is critical to evaluating present and future climate impacts. Thus, the application of in situ measurement approaches, combined with the spatial interpolation methods, will help to explore variations in source contribution to the total CO₂ mixing ratios in the urban atmosphere. This study presents the spatial characteristic and temporal trend of atmospheric CO₂ levels observed within the city of Wroclaw, Poland for the July 2017–August 2018 period. The seasonal variability of atmospheric CO₂ around the city was directly measured at the selected sites using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. The current work aimed at determining the accuracy of the interpolation techniques and adjusting the interpolation parameters for estimating the magnitude of CO₂ time series/seasonal variability in terms of limited observations during the vegetation and non-vegetation periods. The objective was to evaluate how different interpolation methods will affect the assessment of air pollutant levels in the urban environment and identify the optimal sampling strategy. The study discusses the schemes for optimization of the interpolation results that may be adopted in areas where no observations are available, which is based on the kriging error predictions for an appropriate spatial density of measurement locations. Finally, the interpolation results were extended regarding the average prediction bias by exploring additional experimental configurations and introducing the limitation of the future sampling strategy on the seasonal representation of the CO₂ levels in the urban area.

Temporal and spatial distribution of both biogenic and anthropogenic components of atmospheric carbon dioxide (CO₂) and methane (CH₄) is crucial for understanding the environmental impacts of climate change over urban areas. This research focuses on applying stable isotope source-partitioning studies to determine the interactions between biogenic and anthropogenic CO₂ and CH₄ emissions in an average-sized city environment. Study signifies the weight of instantaneous variability and diurnal averaging as compared with seasonal records of variations of the atmospheric CO₂ and CH₄ at a variety of typical urban sites in the city of Wroclaw, conducted during a one-year period from June 2017 to August 2018. The findings reveal distinct temporal variations in atmospheric CO₂ and CH₄ mole fractions and their isotopic composition. The average atmospheric CO₂ and CH₄ mole fractions during the study period were 416.4 ± 20.5 ppm, and 1.95 ± 0.09 ppm, respectively. The study highlights the high variability of driving forces, including current energy use patterns, natural carbon reservoirs, planetary boundary layer dynamics, and atmospheric transport. Additionally, the relationship between the evolution of the convective boundary layer depth and the CO₂ budget was analyzed using the CLASS model with input parameters based on field observations, resulting in insights such as an increase in the range of 25-65 ppm of CO₂ during stable nocturnal boundary layers. The observed changes in stable isotopic signatures of air samples allowed for the identification of two main source categories in the city area: fuel combustion and biogenic processes. The δ¹³C-CO₂ values of collected samples suggest that biogenic emissions dominate (up to 60 % of CO₂ excess mole fraction) during the growing season, but are reduced by plant photosynthesis during summer afternoons. In contrast, local fossil-fuel CO₂ contribution (up to 90 % of excess CO₂ mole fraction) from domestic heating, vehicle emissions, and heat and power plants predominantly influence the urban GHG budget during winter. The δ¹³C-CH₄ values indicate anthropogenic sources related to fossil fuel combustion during winter, with values ranging from -44.2 ‰ to -51.4 ‰, while slightly more depleted values, between -47.1 ‰ and -54.2 ‰, reflect a larger input of biological processes in the methane urban budget during summer. Overall, instantaneous and hourly variability of the above-mentioned readings of gas mole fraction and isotopic composition, have shown higher variability than seasonal amplitudes. Hence, respecting this granularity is the key to alignment and understanding significance of such localized atmospheric pollution studies. Additionally, the changing overprint of the system's framework, such as variability of wind and atmospheric layering patterns, weather events, provides context of sampling and data analysis at different frequencies.

Landfills have been identified as one of the major sources of greenhouse gas (GHG) emissions and as a contributor to climate change. Landfill facilities exhibit considerable spatial and temporal variability of both methane (CH₄) and carbon dioxide (CO₂) rates. The present work aimed to evaluate the spatial distribution of CH₄ and CO₂ and their δ¹³C isotopic composition originating from a municipal landfill site, to identify its contribution to the local GHG budget and the potential impact on the air quality of the immediate surroundings in a short-term response to environmental conditions. The objective was met by performing direct measurements of atmospheric CO₂ and CH₄ at the selected monitoring points on the surface and applying a binary mixing model for the determination of carbon isotopic ratios in the vicinity of the municipal waste landfill site. Air samples were collected and analysed for isotopic composition using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. Kriging and Inverse distance weighting (IDW) methods were used to evaluate the values at unsampled locations and to map the excess of GHGs emitted from the landfill surface. The large off-site dispersion of methane from the landfill site at a 500 m distance was identified during field measurements using isotopic data. The mean δ¹³C of the landfill biogas emitted to the surrounded atmosphere was −53.9 ± 2.2‰, which corresponded well to the microbial degradation processes during acetate fermentation in the waste deposits. The calculated isotopic compositions of CO₂ (δ¹³C = −18.64 ± 1.75‰) indicate the domination of biogenic carbon reduction by vegetation surrounding the landfill. Finally, amounts of methane escaping into the air can be limited by the appropriate landfill management practices (faster covers active quarter through separation layer), and CH₄ reduction can be achieved by sealing the cover on the leachate tank.