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The rapid development of low-cost sensors provides the opportunity to greatly advance the scope and extent of monitoring of indoor air pollution. In this study, calibrated particle matter (PM) sensors and a non-negative matrix factorisation (NMF) source apportionment technique are used to investigate PM concentrations and source contributions across three households in an urban residential area. The NMF is applied to combined data from all houses to generate source profiles that can be used to understand how PM source characteristics are similar or differ between different households in the same urban area. PM 2.5 and PM 10 concentrations in all three houses were greater, more variable, and significantly different to ambient concentrations recorded at a nearby ambient monitoring site. Concentrations were also significantly different between houses, with the World Health Organisation 24-h guideline limits for PM 2.5 breached in one household. The applied methodology was highly successful at modelling concentrations for all the houses (R 2 ≥ 0.983), finding that across the houses the I/O (indoor to outdoor sources ratio) was the lowest for PM 1 (down to 0.08), and greatest for PM 10 (up to 4.93). Whilst the sources could not be clearly distinguished further than being outdoors or indoors, the methodology provides clear insights to source variability within and between the monitored houses. These results highlight the importance of monitoring indoor air pollution to improve pollution exposure estimates, as whilst people may live in areas with acceptable ambient air quality, they can be exposed to unhealthy concentrations in their own homes. This method may be applied in future studies for extended periods to investigate the influence of source seasonality on PM concentrations or scaled up to investigate source variability across larger geographical areas.

New particle formation (NPF) events have different patterns of development depending on the conditions of the area in which they occur. In this study, particle size distributions in the range of 16.6–604 nm (7 years of data) were analysed and NPF events occurring at three sites of differing characteristics – rural Harwell (HAR), urban background North Kensington (NK), urban roadside Marylebone Road (MR), London, UK – were extracted and studied. The different atmospheric conditions in each study area not only have an effect on the frequency of the events, but also affect their development. The frequency of NPF events is similar at the rural and urban background locations (about 7 % of days), with a high proportion of events occurring at both sites on the same day (45 %). The frequency of NPF events at the urban roadside site is slightly less (6 % of days), and higher particle growth rates (average 5.5 nm h−1 at MR compared to 3.4 and 4.2 nm h−1 at HAR and NK respectively) must result from rapid gas-to-particle conversion of traffic-generated pollutants. A general pattern is found in which the condensation sink increases with the degree of pollution of the site, but this is counteracted by increased particle growth rates at the more polluted location. A key finding of this study is that the role of the urban environment leads to an increment of 20 % in N16–20 nm in the urban background compared to that of the rural area in NPF events occurring at both sites. The relationship of the origin of incoming air masses is also considered and an association of regional events with cleaner air masses is found. Due to lower availability of condensable species, NPF events that are associated with cleaner atmospheric conditions have lower growth rates of the newly formed particles. The decisive effect of the condensation sink in the development of NPF events and the survivability of the newly formed particles is underlined, and influences the overall contribution of NPF events to the number of ultrafine particles in an area. The other key factor identified by this study is the important role that pollution, both from traffic and other sources in the urban environment (such as heating or cooking), plays in new particle formation events.

Successful air quality management and control not only requires measurements of air pollution levels. It also requires information on the sources of air pollution, and their relative magnitudes and importance, to plan and enact cost-effective control measures. This paper provides an important breakthrough towards the wider and more comprehensive use of source apportionment via low-cost techniques. Low-cost sensor measurements, along with the statistical methods of Positive Matrix Factorization (PMF) and k -means clustering, were able to successfully pinpoint and quantify the main sources of pollution in three regulatory important sites (a construction site, a quarry and a roadside). The anticipated levels of pollution, which were dependent on meteorological conditions and temporal variations, were assessed. The analysis provides information crucial for successful air quality management and control at a significantly lower cost than previously achieved. The strengths and weaknesses of the methodologies used are illustrated and discussed.

Particulate Matter (PM) air pollution poses significant threats to public health. We introduce a novel machine learning methodology to predict PM 2.5 levels at 30 m long segments along the roads and at a temporal scale of 10 seconds. A hybrid dataset was curated from an intensive PM campaign in Selly Oak, Birmingham, UK, utilizing citizen scientists and low-cost instruments strategically placed in static and mobile settings. Spatially resolved proxy variables, meteorological parameters, and PM properties were integrated, enabling a fine-grained analysis of PM 2.5 . Calibration involved three approaches: Standard Random Forest Regression, Sensor Transferability and Road Transferability Evaluations. This methodology significantly increased spatial resolution beyond what is possible with regulatory monitoring, thereby improving exposure assessments. The findings underscore the importance of machine learning approaches and citizen science in advancing our understanding of PM pollution, with a small number of participants significantly enhancing local air quality assessment for thousands of residents.

Low-cost particle sensors have proven useful in applications such as source apportionment, health, and reactivity studies. The benefits of these instruments increase when used in parallel, as exemplified with a 3-month long deployment in an urban background site. Using two lung-deposited surface area (LDSA) instruments, a low-cost method was developed to assess the solid component of an aerosol by applying a catalytic stripper to the inlet stream of one LDSA instrument, resulting in only the solid fraction of the sample being measured (LDSAc). To determine the semi-volatile fraction of the sample, the LDSAC was compared to the LDSA without a catalytic stripper, thus measuring all particles (LDSAN). The ratio of LDSA (LDSAC/LDSAN) was used to assess the fraction of solid and semi-volatile particles within a sample. Here, a low ratio represents a high fraction of semi-volatile particles, with a high ratio indicating a high fraction of solid particles. During the 3-month urban background study in Birmingham, UK, it is shown that the LDSA ratios ranged from 0.2–0.95 indicating a wide variation in sources and subsequent semi-volatile fraction of particles. A black carbon (BC) instrument was used to provide a low-cost measure of LDSA to BC ratio. Comparatively, the LDSA to BC ratios obtained using low-cost sensors showed similar results to high-cost analyses for urban environments. During a high LDSAC/LDSAN ratio sampling period, representing high solid particle concentrations, an LDSA to BC probability distribution was shown to be multimodal, reflecting urban LDSA to BC ratio distributions measured with laboratory-grade instrumentation. Here, a low-cost approach for data analyses presents insight on particle characteristics and insight into PM composition and size, useful in source apportionment, health, and atmospheric studies.

Indoor air quality (IAQ) is increasingly recognised as one of the most important aspects for public health, workplace safety and productivity. While indoor and outdoor factors both influence indoor pollutant levels, human presence and activity are key drivers of the emission of specific pollutants, including particulate matter (PM), total volatile organic compounds (TVOCs) and carbon dioxide (CO 2 ). This study investigates the relationship between occupancy, physical activity measured by kinetic energy (KE), and air pollution concentrations in a real-world office setting, by combining data from air quality and radar motion sensors. Two exemplar office spaces were investigated, comprising an open-office area and a meeting room. PM, in the PM 1 and PM 2.5 size fractions, were found to be highly correlated with the outdoor conditions, whereas PM 10 correlates more closely with indoor occupancy (up to r  = 0.65). Even higher correlations, up to r  = 0.74, were found between human activity, quantified as KE, and the PM 10 concentrations. The TVOCs and CO 2 showed even stronger correlations with KE (up to r  = 0.83), suggesting that these metrics can be used as excellent proxies for estimating certain types of indoor air pollution. Notably, the impact of additional occupants varies depending on room characteristics and usage, underscoring the need for contextualised models of IAQ. By quantifying both outdoor infiltration and indoor emissions, this study offers a framework for disentangling pollutant sources and guiding interventions to optimise IAQ. These insights support evidence-based strategies to create healthier and more productive office environments.

Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low‐cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low‐cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM 2.5 and PM 10 mass concentrations of 14.4 and 51.0  μ g/m 3 , respectively. During school hours, when students were present, all classrooms had average PM 2.5 concentrations greater than 8.1  μ g m −3 and average PM 10 concentrations greater than 13.1  μ g m −3 . Notably, the English studies classroom exceeded the 24‐h WHO ambient PM 10 guideline (45  μ g m −3 ). Employing the non‐negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM 1 observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM 2.5 , and 19%–40% of PM 10 , respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. Thereby, it allows for air quality management in locations crucial for the public health and educational outcomes of children.

Although new particle formation (NPF) events have been studied extensively for some decades, the mechanisms that drive their occurrence and development are yet to be fully elucidated. Laboratory studies have done much to elucidate the molecular processes involved in nucleation, but this knowledge has yet to be conclusively linked to NPF events in the atmosphere. There is great difficulty in successful application of the results from laboratory studies to real atmospheric conditions due to the diversity of atmospheric conditions and observations found, as NPF events occur almost everywhere in the world without always following a clearly defined trend of frequency, seasonality, atmospheric conditions, or event development. The present study seeks common features in nucleation events by applying a binned linear regression over an extensive dataset from 16 sites of various types (combined dataset of 85 years from rural and urban backgrounds as well as roadside sites) in Europe. At most sites, a clear positive relation with the frequency of NPF events is found between the solar radiation intensity (up to R2=0.98), temperature (up to R2=0.98), and atmospheric pressure (up to R2=0.97), while relative humidity (RH) presents a negative relation (up to R2=0.95) with NPF event frequency, though exceptions were found among the sites for all the variables studied. Wind speed presents a less consistent relationship, which appears to be heavily affected by local conditions. While some meteorological variables (such as the solar radiation intensity and RH) appear to have a crucial effect on the occurrence and characteristics of NPF events, especially at rural sites, it appears that their role becomes less marked at higher average values. The analysis of chemical composition data presents interesting results. Concentrations of almost all chemical compounds studied (apart from O3) and the condensation sink (CS) have a negative relationship with NPF event frequency, though areas with higher average concentrations of SO2 had higher NPF event frequency. Particulate organic carbon (OC), volatile organic compounds (VOCs), and particulate-phase sulfate consistently had a positive relation with the growth rate of the newly formed particles. As with some meteorological variables, it appears that at increased concentrations of pollutants or the CS, their influence upon NPF frequency is reduced.

Delhi is one of the world's most polluted cities, with very high concentrations of airborne particulate matter. However, little is known about the factors controlling the characteristics of wide-range particle number size distributions. Here, new measurements are reported from three field campaigns conducted in winter and pre-monsoon and post-monsoon seasons at the Indian Institute of Technology campus in the south of the city. Particle number size distributions were measured simultaneously, using a scanning mobility particle sizer and a GRIMM optical particle monitor, covering 15 nm to >10 µm diameter. The merged, wide-range size distributions were categorized into the following five size ranges: nucleation (15–20 nm), Aitken (20–100 nm), accumulation (100 nm–1 µm), large fine (1–2.5 µm), and coarse (2.5–10 µm) particles. The ultrafine fraction (15–100 nm) accounts for about 52 % of all particles by number (PN10 is the total particle number from 15 nm to 10 µm) but just 1 % by PM10 volume (PV10 is the total particle volume from 15 nm to 10 µm). The measured size distributions are markedly coarser than most from other parts of the world but are consistent with earlier cascade impactor data from Delhi. Our results suggest substantial aerosol processing by coagulation, condensation, and water uptake in the heavily polluted atmosphere, which takes place mostly at nighttime and in the morning hours. Total number concentrations are highest in winter, but the mode of the distribution is largest in the post-monsoon (autumn) season. The accumulation mode particles dominate the particle volume in autumn and winter, while the coarse mode dominates in summer. Polar plots show a huge variation between both size fractions in the same season and between seasons for the same size fraction. The diurnal pattern of particle numbers is strongly reflective of a road traffic influence upon concentrations, especially in autumn and winter, although other sources, such as cooking and domestic heating, may influence the evening peak. There is a clear influence of diesel traffic at nighttime, when it is permitted to enter the city, and also indications in the size distribution data of a mode < 15 nm, which is probably attributable to CNG/LPG vehicles. New particle formation appears to be infrequent and is, in this dataset, limited to 1 d in the summer campaign. Our results reveal that the very high emissions of airborne particles in Delhi, particularly from traffic, determine the variation in particle number size distributions.

New particle formation (NPF) events occur almost everywhere in the world and can play an important role as a particle source. The frequency and characteristics of NPF events vary spatially, and this variability is yet to be fully understood. In the present study, long-term particle size distribution datasets (minimum of 3 years) from 13 sites of various land uses and climates from across Europe were studied, and NPF events, deriving from secondary formation and not traffic-related nucleation, were extracted and analysed. The frequency of NPF events was consistently found to be higher at rural background sites, while the growth and formation rates of newly formed particles were higher at roadsides (though in many cases differences between the sites were small), underlining the importance of the abundance of condensable compounds of anthropogenic origin found there. The growth rate was higher in summer at all rural background sites studied. The urban background sites presented the highest uncertainty due to greater variability compared to the other two types of site. The origin of incoming air masses and the specific conditions associated with them greatly affect the characteristics of NPF events. In general, cleaner air masses present higher probability for NPF events, while the more polluted ones show higher growth rates. However, different patterns of NPF events were found, even at sites in close proximity (< 200 km), due to the different local conditions at each site. Region-wide events were also studied and were found to be associated with the same conditions as local events, although some variability was found which was associated with the different seasonality of the events at two neighbouring sites. NPF events were responsible for an increase in the number concentration of ultrafine particles of more than 400 % at rural background sites on the day of their occurrence. The degree of enhancement was less at urban sites due to the increased contribution of other sources within the urban environment. It is evident that, while some variables (such as solar radiation intensity, relative humidity, or the concentrations of specific pollutants) appear to have a similar influence on NPF events across all sites, it is impossible to predict the characteristics of NPF events at a site using just these variables, due to the crucial role of local conditions.