Statistical learning models have been applied to study the spatial patterns of ambient Nitrogen Dioxide (NO2), which is a highly dynamic, traffic-related air pollutant. Commonly, the validation process in most studies is based on bootstrapped split-sampling of training and test sets from fixed ground station measurements. As the ground stations distribute mostly sparsely over a region or country, this kind of cross-validation validation method does not consider how well models are capable of representing spatial variations in air pollution mostly occurring over distances shorter than the ground station sampling spacing. This may lead to inadequate hyperparameter optimisation and bias when comparing different statistical models. External mobile measurements are therefore needed for more reliable model evaluations as these provide detailed and spatially continuous information on air pollution patterns. However, most current designs of mobile NO2 sensing instruments suffer from the trade-off between flexibility and measurement accuracy, as high-end sensors are commonly too heavy to be carried by a person or on a bike. In addition, sufficient repetitions over time are needed so that the measurements are representative to concentrations over a relatively long-term period. In this study, we installed a mobile air quality station onboard a cargo-bike to collect a dataset suitable for external validation. With the external validation dataset the model hyperparameter setting and statistical model comparison results alter. Our model comparison results also differ from previous studies relying only on ground stations for cross-validation.

Cities in southern Chile are facing high levels of PM₂.₅ because of wood burning pollution. We quantify the contribution of wood smoke to fine particles in two mid-size cities: Molina and Valdivia, located in different climate zones. The sampling campaigns were carried out during austral winter (July to September) in 2018 (Molina) and 2019 (Valdivia). 24-h filter samples were analyzed for carbonaceous compounds, secondary ions, metals, and particle-phase organic molecular markers. Average winter concentrations of PM₂.₅ were 53 ± 32 μg/m³ (average ± standard deviation) in Molina and 89 ± 55 μg/m³ in Valdivia. The major component of fine particles was organic matter, representing more than 70% of PM₂.₅. Concentrations of organic molecular markers were used in a receptor model (US EPA CMB8.2) to identify and quantify primary sources of PM₂.₅. The major source of PM₂.₅ was wood smoke, which accounted for 41.55 ± 9.77 μg/m³ (62.9 ± 15.3%) in Molina and 43.65 ± 24.06 μg/m³ (51.7 ± 21.1%) in Valdivia. Secondary organic aerosols (SOA) generated from inefficient wood burning, contributed 20.4 ± 17.7% in Molina and 28.9 ± 27.6% in Valdivia. Secondary inorganic ions and dust are minor sources of PM₂.₅. The total contribution of wood smoke (adding primary wood smoke and SOA) could be as much as 83% in Molina and 81% in Valdivia, during the winter season.

Solar eclipse (with maximum obscuration of 85.3% and magnitude of 0.893) occurred on 26 December 2019 during morning hours (08:10 to 11:15 LT with a peak at 09:33 LT) over Gadanki (13.5ᵒN, 79.2ᵒE) has provided a unique opportunity to test the hypothesis of ‘Extended Fumigation Effect’ or ‘Second Fumigation’ on the surface and boundary layer pollutants. To capture this event, a campaign using multi-instrument (AWS, Aethalometer, PM sensors, ceilometer, radiosonde) on multi-platform (surface, surface based remote sensing, drone, tethered balloon, in-situ balloon) was conducted. Eclipse obscuration caused decrease in surface temperature by 4.3 °C around 10:00 LT. Boundary layer remained shallow until 09:00 LT (between 500 m and 900 m) but near the termination of the eclipse and soon after the termination a convective boundary layer showed a rapid increase to above 1 km within a short time (1 h). A Fumigation peak (common phenomenon in normal days) in black carbon occurred with a sharp peak concentration of 9.4 μg/m³ at around 07:00 LT and then started decreasing. However, concentration started to increase unusually again at around 08:20 LT and remained at the range of 4–6 μg/m³instead of a normal decreasing trend, which is about 2–3 times of the mean concentration at this period of time. Similar variation in PM₁, PM₂.₅, and PM₁₀are also observed. Background instability estimated using radiosonde measurements suggests Fumigation, Fumigation/Lofting and Trapping before, during and after the eclipse, respectively.

The UK may be required to expand its bioenergy production in order to make a significant contribution towards the delivery of its ‘net zero’ greenhouse gas emissions target by 2050. However, some trees grown for bioenergy are emitters of volatile organic compounds (VOCs), including isoprene and terpenes, precursors in the formation of tropospheric ozone, an atmospheric pollutant, which require assessment to understand any consequent impacts on air quality. In this initial scoping study, VOC emission rates were quantified under UK climate conditions for the first time from four species of eucalypts suitable for growing as short-rotation forest for bioenergy. An additional previously characterised eucalypt species was included for comparison. Measurements were undertaken using a dynamic chamber sampling system on 2-3 year-old trees grown under ambient conditions. Average emission rates for isoprene, normalised to 30 °C and 1000 μmol m⁻² s⁻¹ PAR, ranged between 1.3 μg C gdw⁻¹ h⁻¹ to 10 μg C gdw⁻¹ h⁻¹. All the eucalypt species measured were categorised as ‘medium’ isoprene emitters (1–10 μg C gdw⁻¹ h⁻¹). Total normalised monoterpene emission rates were of similar order of magnitude to isoprene or approximately one order of magnitude lower. The composition of the monoterpene emissions differed between the species and major compounds included eucalyptol, α-pinene, limonene and β-cis-ocimene. The emission rates presented here contribute the first data for further studies to quantify the potential impact on UK atmospheric composition, if there were widespread planting of eucalypts in the UK for bioenergy purposes.

In Turkey, Southeastern Anatolia region is the highest in terms of solar radiation level. However, the provinces in the region are subject to Particulate Matter (PM) coming from the Sahara desert, the Syrian Desert and the Arabian Desert by atmospheric transport. The daily limit of PM₁₀ and PM₂.₅ set by WHO for health is often exceeded in Sanliurfa. PM₁₀ and PM₂.₅ pollutants also accumulate on the Photovoltaic (PV) panels and cause loss of PV panel performance. In this study, the effects of atmospheric dust deposition on the performance of PV panel was determined for both monocrystalline and polycrystalline technologies under Sanliurfa atmospheric conditions. Two panels with the same characteristics were used for each PV panel group from 2 different PV technologies. One of the panels in the group was cleaned by washing with distilled water every Monday while the other was not cleaned. Thus, the effect of the dust accumulation on the PV panel was determined by comparison to the cleaned PV panel. PV panel power is measured with I–V meter. Panel surface temperature, solar radiation and other meteorological parameters are measured simultaneously. The measurements were done every Monday, Wednesday and Friday at 12:00 am from May 1 to December 31, 2019. It is observed that the dust accumulation reduces the PV power output up to 8% depending on the amount of radiation. During the summer months, the power loss on the average is 4.33% for monocrystalline and 4.57% for polycrystalline. In the autumn months, it is less than 1.77%.

This study investigates the contents, distribution patterns, and sources of lanthanoid elements (La to Lu) in aerosols with an aerodynamic diameter ≤10 μm (PM₁₀) in a coastal Caribbean region in order to better constrain the origin of the atmospheric PM contamination. We sampled and analysed PM₁₀ aerosols during 2015 simultaneously at a rural and an urban site in Cienfuegos (Cuba) as well as particles samples from regional contamination sources. Results showed that the sum of the studied lanthanoids concentrations ranged from 0.03 to 13.42 ng m⁻³ and from 0.51 to 18.75 ng m⁻³ at the rural and the urban site, respectively. Time variations for the lanthanoid concentrations displayed similar trends and showed that the highest concentrations corresponded to the influence of the African dust for both sites, but presented distinct variability and lower concentrations when dust intrusions were less frequent. The lanthanoid distribution patterns in the rural and urban sites were significantly different, due to the impact of different local combustion sources. Our results were comforted by comparing the degree of fractionation of the lighter and heavier lanthanoids and the δEu and δCe anomalies between our PM₁₀ samples and those of the local sources of contamination. Ultimately, we highlight the added value of lanthanoid elements as reliable indicators for discriminating emission sources and for tracking the origin of atmospheric particulate matter.

In this paper, we investigate the footprint of the operation of Athens International Airport in loads of air pollutants emitted during the Landing-Take Off phase of incoming and outgoing flights. This part of the flight has the distinctive characteristic that it operates in the human environment, at low altitudes, so it directly affects the air quality at the airport and its surroundings by changing the total amounts of air pollutants involved. The present survey covers the period 2002–2019 and only civil aircrafts flights have been considered. In particular, the concentrations mono-nitrogen oxides (NOX), carbon monoxide (CO), carbon dioxide (CO₂), unburnt hydrocarbons (HC) and total Particulate Matter (PM) consisting of volatile organic PM, volatile sulphuric PM and non-volatile PM have been studied. According to the results obtained more than 6500 kt of CO₂, almost 28 kt of NOX, about 18 kt of CO, almost 1.5 kt of HC and 0.3 kt of PMₜₒₜₐₗ have been released into the atmosphere during the total operating time of the airport. Actions related to the conduct of new measurements of air pollutants are aimed which point to the reduction of their impacts in the coming years.

This study presents a method for “downscaling” aggregated global emissions of CO, NOₓ, and PM₂.₅ based on georeferenced information (spatial proxies). We distribute ECLIPSE-CLE emissions for Quito, Ecuador, in 2015 and 2017. The study area is a grid of 0.5 × 0.5 km² cells over a 110 × 110 km² area. The emission sectors (proxies in parenthesis) are agricultural (land-use maps), domestic (land-use and population density), energy, industry, and waste disposal (point source location from local inventory), and transport (population, vehicle traffic, and road density). Emission distribution quality is satisfactorily evaluated (graphically and statistically) by implementing them in the UBM model and comparing modeled concentrations with observations. This study also explores an alternative proxy set-up for main road emissions based on road density, which, for some modeling sites, results in a better agreement with the observations. Finally, this methodology is applied for comparing air pollution due to two urban growth types for Quito in 2040: sprawl and densification. Both scenarios lead to lower concentrations than in 2017, except for O₃. Although the two scenarios attain similar concentrations, urban sprawl presents, in general, noticeably higher values for NOₓ and NO₂.

Emission characteristics of biogenic volatile organic compounds (BVOCs) (such as isoprene and monoterpenes) emitted from major species of street trees and urban forests by variations in temperature and photosynthetically active radiation (PAR) were investigated. The isoprene and monoterpene emission rates from Prunus sargentii, Ginkgo biloba, Zelkova serrata and Taxus cuspidata were meager. In contrast, the isoprene and monoterpene emission rates from Metasequoia glyptostroboides were very high. In particular, the emission of α-pinene from Metasequoia glyptostroboides was over 10,000 times higher than that from Ginkgo biloba. The patterns of isoprene emissions from the four tree species except for Metasequoia glyptostroboides concerning temperature and PAR were difficult to determine because the emission rate is very low. However, monoterpene emissions from all five tree species were clearly affected by temperature and PAR. These results showed that the characteristics of isoprene and monoterpene emissions differed depending on the tree species. Regarding monoterpene composition, α-pinene (81.3%) accounts for the majority of total monoterpenes from Metasequoia glyptostroboides. This could be a critical consideration when planting trees in an urban forest because BVOC emissions (e.g., α-pinene) have been well known to affect ground-level ozone formation rate via photochemical reaction with NOX. Since Metasequoia glyptostroboides showed relatively high BVOC emissions, the use of this type of tree in an urban forest with relatively high nitrogen oxide emissions should be carefully considered.

Understanding and quantifying the influence of volatile organic compounds (VOCs) on ozone and secondary organic aerosol formation is essential for better prediction/estimation of these products. A total of 9 VOCs along with surface ozone were measured during the year 2019 at Pune (India) location. The ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) estimations are compared for 2 methods-using measured VOC concentrations and using their photochemical initial concentrations (PIC). The OFP and SOAFP estimated based on the measured VOC concentrations provide an incomplete understanding of these 2 formation processes. This is mainly because measured VOCs don't account for the photochemical losses that compounds undergo from the source to the receptor. The PIC values of VOCs have been estimated in this study to highlight the importance of considering the photochemical losses. For example, the PIC value of highly reactive compound, isoprene, was found to be 152% higher (1.48 ppbv) than its measured value (0.59 ppbv). The resultant total OFP estimate based on PIC values of all the VOCs was found to be 53.30 ± 35.02 ppbv as compared to 45.99 ± 29.35 ppbv obtained from measured VOCs. Based on k-means clustering analysis, it was found that the highest ozone formation was favored under transition regime chemistry when PIC values were considered. The average total SOAFP based on PIC values was found to be 1.32 ± 1.40 ppbv, while it was 1.17 ± 1.18 ppbv for measured VOCs. The aromatics contributed to over 90% of total SOAFP estimated for the region.