Exposure to particulate air pollution increases total natural and cardiovascular mortality. However, it is less clear which types and sources of particles are the most harmful. We analyzed associations between long-term exposure to source-specific locally emitted particles and total natural and cardiovascular mortality in Swedish cohorts. Using high-resolution dispersion models of particles from different sources, and address registries, we assigned annual individual residential mean concentrations to population-based cohorts in Gothenburg, Stockholm and Umeå 1990-2011. Time and cause of death were assigned from registries. Associations between long-term mean lagged exposures and mortality were estimated using Cox regression models adjusted for possible confounders, and meta-analyzed. 7344 natural deaths, including 2755 cardiovascular deaths, occurred among the 68,679 participants. Exposure levels were moderate but generally above the WHO 2021 guidelines. We observed positive associations with natural mortality for the last five years of exposure to road traffic exhaust particles (HR 1.02, 95% CI 1.00-1.04, per IQR, and 1.10, 95% CI 1.00-1.22, per 1 µg/m3), and road wear particles (HR 1.02, 95% CI 1.00-1.04, per IQR, and HR 1.02, 95% CI 1.00-1.03, per 1 µg/m3), but not for particles from residential heating. Adjustment for road traffic noise, or particles from residential heating, did not substantially affect the results for traffic-related particles. For cardiovascular mortality, associations with particles from both sources were positive but not statistically significant. Natural mortality was associated with local emissions of traffic-related particles in a multi-cohort study at moderate exposure-levels, lending some support for further efforts to reduce traffic emissions.

Air pollution is a major global threat to health. The study aimed to analyze the chemical composition of PM2.5 in Mabopane, South Africa, and to identify the contribution of transported particulate pollution sources using backward air transport cluster analysis. PM2.5 samples were collected for 24 h every 6 days from June 15, 2022 to February 28, 2023. PM2.5, soot, black carbon (BC), organic carbon (OC), and elemental concentrations were measured. The mean PM2.5 and soot were 10 mu gm-3 and 1 x 10-5 m-1, respectively, exceeding the WHO annual limit but below the 24-h SANAAQS. BC and OC levels were 0.9 and 1.0 mu gm-3, respectively. Elements determined by Energy Dispersive X-Ray Fluorescence (EDXRF) included Ag, Ba, Br, Ca, Cl, Cu, Fe, K, Mn, Ni, P, S, Sb, Si, Sr, Ti, U, V, and Zn, with Fe, S, K, Ca, and Si being the most abundant. PM2.5 in Mabopane is influenced by local and transported sources, highlighting the need for stronger, coordinated air quality management and monitoring.

We analyze how the introduction of congestion charges in Gothenburg, Sweden, in 2013 affected the prices of condominiums. Using both a hedonic difference-in-difference (DiD) price regressions and the regression discontinuity design (RDD) approach we find robust evidence that the congestion charges made condominiums inside the toll zone less attractive. For instance, the findings from the DiD suggest a negative price impact on condominiums within the zone by about 6 percent compared to the control group (condominiums in Gothenburg outside the toll zone). The conclusion is that there is strong evidence that the congestion charges had a negative effect on property prices within the toll zone in Gothenburg. This can be explained by relatively small positive effects on traffic volumes and the environment within the zone.

This study investigated fine particulate matter (PM2.5) in Welkom, South Africa, a legacy mining town. PM2.5 was sampled over 12 months at two sites, an Industrial Site and a Residential Site located only 5.6 km apart, to assess total concentrations, PM2.(5) chemical composition, soot, black carbon (BC), UV-absorbing particulate matter (UV-PM), and the geographical origin of air masses. At the Industrial Site, the annual mean PM2.5 concentration was 14.7 & micro;g/m & sup3; (0.17-66.3 & micro;g/m & sup3;), while the Residential Site recorded a markedly lower mean of 6.47 & micro;g/m & sup3; (0.17-24.3 & micro;g/m & sup3;). Mean soot levels were 1.07 & times; 10(-5) m(-1) (0.01-5.52 & times; 10(-5) m(-1)) at the Industrial Site and 1.10 & times; 10(-5) m(-1) (0.014-5.50 & times; 10(-5) m(-1)) at the Residential Site. BC concentrations averaged 1.9 & micro;g/m & sup3; (0.028-8.01 & micro;g/m & sup3;) at the Industrial Site and 0.6 & micro;g/m & sup3; (0.2-2.8 & micro;g/m & sup3;) at the Residential Site. UV-PM averaged 1.6 & micro;g/m & sup3; (0.006-5.22 & micro;g/m & sup3;) at the Industrial Site and 0.8 & micro;g/m & sup3; (0.1-3.1 & micro;g/m & sup3;) at the Residential Site. Clustered back-trajectory analysis further showed that northerly and easterly air masses carried the highest PM2.5, soot, BC, and UV-PM levels. Across all pollutants, higher concentrations at the Industrial Site highlight the influence of local combustion sources, resuspended dust, and industrial activities.

Fine particulate matter (PM2.5) drives millions of global premature deaths via respiratory and systemic effects, exacerbated by bound trace elements. In South Africa, studies prioritize metros, overlooking midsized cities like Bloemfontein, where biomass burning, industry, and dust elevate pollution. The first age-stratified inhalation health risk assessment of PM2.5 and trace elements in this setting was conducted using samples collected over 14 months (June 2020-August 2021) at Pelonomi Hospital and University of the Free State (UFS). Gravimetric analysis measured mass; and energy-dispersive X-ray fluorescence quantified trace elements from UFS samples. U. S. EPA methods assessed non-carcinogenic (hazard quotients, HQs) and carcinogenic risks (CRs) for infants, children, and adults. Annual PM2.5 averaged 6 µ m-3 at Pelonomi (12× WHO's 5 µg m-3 guideline) and 11 µg m-3 at UFS (2.2×). Vanadium (V) showed the highest non-carcinogenic risk across ages, and chromium (Cr) had a CR of 4.32 × 10-5. V ranked Category A (priority), while Cl, Mn, Si, S, Cr, Ni, Fe, and Cu ranked Category B. Winter increased PM2.5 concentrations and associated risks by 40%, underscoring regulatory shortfalls and the need for emission controls, clean energy transitions, and alignment of national standards with WHO guidelines to reduce pediatric risks (SDGs 3, 7, 11).

PM2.5 is associated with multiple adverse health outcomes, yet data on its concentration, composition and sources in African cities remain limited. This study presents the first detailed characterisation of outdoor PM2.5 in Johannesburg, South Africa. Twenty-four-hour filter samples were collected every sixth day from 3 October 2020 to 12 October 2021 at a residential site in the suburb of Buccleuch. Samples were analysed using gravimetric methods, smoke-stain reflectometry, optical transmissometry and X-ray fluorescence. Source contributions were assessed using principal component analysis (PCA), enrichment factor (EF) analysis and Hybrid Single Particle Lagrangian Integrated Trajectory model for backward trajectories. The mean PM2.5 concentration was 8.1 µg.m−3(range: 0.04–30 µg.m−3), exceeding the World Health Organization (WHO) annual guideline (5 µg.m−3). Daily concentrations surpassed the WHO daily guideline (15 µg.m−3) on seven of the 55 sampling days. Mean black carbon (BC) and organic carbon (OC) concentrations were 0.51 and 0.46 µg.m−3, respectively. Twelve trace elements were detected, with Fe, K, S and Si most abundant. PM2.5, BC, OC and several elements were significantly higher in winter and autumn, reflecting increased combustion activities and unfavourable meteorological conditions. Trajectory analysis indicated contributions from regional mining and coal-related activities. Integrated PCA and EF results showed that PM2.5 comprised resuspended dust, traffic-related non-exhaust emissions, local residential combustion and regionally transported pollution. These findings highlight multi-source exposure and the need for coordinated air quality management at municipal and regional scales.

Sustainable air quality governance requires robust monitoring and updated air quality management plans (AQMPs) to translate legislation into meaningful environmental and health protection. The Highveld Priority Area (HPA), which was declared South Africa's second National Air Pollution Priority Area in 2007, includes the Ekurhuleni Metropolitan Municipality (EMM), where AQMPs are outdated and long-term chemical characterization data remain limited. This study provides baseline evidence to support AQMP revision by characterizing PM2.5 mass concentrations and chemical composition in a residential area of Kempton Park within the EMM and HPA. A total of 57 24 h PM2.5 samples were collected every sixth day from May 2021 to April 2022. Concentrations ranged from 0.9 to 32 & micro;g/m(3) (annual mean 10 & micro;g/m(3)), exceeding the WHO annual guideline (5 & micro;g/m(3)) but remaining below the South African standard (20 & micro;g/m(3)). The daily WHO guideline (15 & micro;g/m(3)) was exceeded on 13 days. PM2.5, black carbon and organic carbon peaked during winter and spring, consistent with enhanced atmospheric stability and combustion emissions, while elements Br, Fe, K, S, Si and Sr exhibited seasonal variability. Principal component analysis and enrichment factor assessment distinguished crustal sources (Si, Ca, Fe, Ti) from enriched anthropogenic elements (S, Zn, Br, U), indicating contributions from combustion, industrial activities and mining. Correlation patterns and 72 h back-trajectory analysis further demonstrated shared sources and significant regional transport influences. These findings highlight the combined role of local emissions, meteorology and long-range transport, providing locally relevant evidence to inform sustainable air quality management within the EMM and HPA.

Air pollution is a major threat to human health globally. In 2021, the World Health Organization (WHO) reported that 7 million prematuredeaths, mainly from non-communicable diseases, are due to air pollution. Air quality studies on PM2.5 and its composition are lackingin South Africa and Africa. To find ways to reduce PM2.5 sources and its associated health impact in the Bojanala Platinum DistrictMunicipality (BPDM), North West province, South Africa, it is necessary to determine PM2.5 concentrations, its chemical compositionand distant air pollution source areas in this area. PM2.5 filter samples were collected manually during 24 hours every sixth day from 10May 2021 and 4 June 2022 in a residential area in Bapong. Bapong is located in the BPDM. The average PM2.5 level during the samplingperiod was 21 μg.m-3 (range: 2.0 to 78 μg.m-3), which is higher than the yearly WHO guideline (5 μg.m-3), and South African NationalAmbient Air Quality Standards (SANAAQS) (20 μg.m-3). The 24-hour PM2.5 levels exceeded the daily WHO guideline (15 μg.m-3) and dailySANAAQS (40 μg.m-3) on 27 and nine occasions, respectively. The highest PM2.5 levels were observed during the cold autumn season(78 μg.m-3: May 2022). Soot levels ranged from 0.1 to 8.0 m-1 × 10-5 with an annual average of 1.8 m-1 × 10-5. The black carbon (BC) levelsranged from 0.1 to 6.0 μg.m-3 with an average of 1.3 μg.m-3. The average level of organic carbon (OC) was 1.4 μg.m-3 (range: 0.1 to 5.0μg.m-3). Most of the geographical air masses were found to be originating inland (65%). This pioneering study in Bapong provideskey insights into the seasonal and weekly variation of PM2.5, soot, BC and OC concentrations, distant air pollution source areas thatcontribute to their concentrations and their potential public health risk in the area.

Background Outdoor particulate air pollution is classified as causing lung cancer, but evidence on specific pollutants and exposure timing remains limited. Methods 22,294 participants in the population-based Malmö Diet and Cancer cohort, were enrolled between 1991 and 1996 and followed until 2016. Incident lung cancer cases were identified through national registers. Annual residential exposure to PM2.5, PM10, black carbon (BC), and nitrogen oxides (NOx) was estimated using high-resolution dispersion models and assigned based on residential history. Time-dependent Cox regression models with age as the time scale were used to estimate hazard ratios (HRs) and confidence intervals (CIs) for lung cancer incidence for exposure at baseline (1990–1994), the five years preceding diagnosis or censoring (lag 1–5), and the 6–10 years prior (lag 6–10). Models were progressively adjusted for smoking (status, intensity, duration), environmental tobacco smoke, employment, occupation, education, physical activity, cohabitation, and area-level socioeconomic status. Results During 325,966 person-years, 499 participants developed lung cancer. In models adjusted for age, sex, and calendar time, positive associations were observed for PM2.5, PM10, BC and NOx. Adjustment for smoking substantially attenuated the estimates leading to imprecise and not statistically significant associations. For example, the HR for PM2.5 (lag 1–5 years) was 1.03 (95% CI: 0.48–2.19) per 5 µg/m³, PM10 (lag 1–5 years) was 1.21 (95% CI: 0.51–2.89) per 10 µg/m³, and for BC (lag 1–5 years) was 1.10 (95% CI: 0.67–1.80) per 0.5 µg/m³, while associations with NOx were close to null. Discussion and conclusion We observed suggestive but imprecise associations between long-term PM exposure and lung cancer incidence. The attenuation after adjustment for smoking highlights the importance of careful confounder control. Overall, findings do not provide strong evidence of an independent association in this low-exposure setting and should be interpreted cautiously.

Source apportionment through factorization is a common method for identifying sources of air pollution. Both PCA and DN-PMF have assumptions, strengths, and limitations. Assigning sources to factors is inherently subjective and can introduce bias. PCA for the number of sources, C-PMF and DN-PMF is performed on data from three cities which were sampled at the same time, 16 April 2017 to 18 April 2018. The DN-PMF was able to give seasonal information to support the source apportionment. Results of the PCA included 6 factors for Thohoyandou and Pretoria and 7 factors for Cape Town. At the two large city sites, the C-PMF presented a dominant coal emissions source (29% and 35.6%) yearly and a strong biomass source during winter (24% and 17%). The dominant yearly source shifted to vehicular emissions with the DN-PMF model in Pretoria and Cape Town (41% and 12%) and coal burning at Thohoyandou (33%). By considering the mixing layer and meteorological conditions the factors shifted while keeping the dominant Cl-Pb and Cu-Zn tracer combinations.

Numerous health outcomes have been attributed to PM2.5 exposure, even at low concentrations, from studies in developed countries. There is a lack of studies in Africa that reported on PM2.5, PM2.5 absorbance (soot), BC, UV-PM (organic carbon) and trace element concentrations and their health effects. PM2.5 samples were collected over 24 h and every third day at an urban background site in Cape Town during 18 April 2017 to 16 April 2018. The mean PM2.5 concentration was 13 µg.m-3 (range: 1.2-39 µg.m-3). PM2.5 concentrations exceeded the yearly World Health Organization (WHO) air quality guideline (5 µg.m-3). The daily WHO guideline (15 µg.m-3) was exceeded on 38 occasions during the 121-day study period. The mean soot, black carbon and organic carbon concentrations were 1.4 m-1 x 10-5, 2.5 µg.m-3 and 2.4 µg.m-3, respectively. Eight trace elements (Ca, Cl, Fe, K, S, Si, Ti and Zn) were detected with high signal to noise ratios. The observed exposure levels at this urban background site, if believed to be experienced across the city, may pose a risk to human health.

Atmospheric fine particulate matter (PM2.5) contributes to approximately 4 million premature deaths globally each year. This study aimed to investigate the health risks of atmospheric PM2.5 and its trace elements in Mabopane, South Africa. PM2.5 samples were collected every sixth day from June 15, 2022 to February 28, 2023 using a GilAir-5 sampler at 4.0 L/min on the Mabopane Fire Station rooftop. Health risks were evaluated using US EPA guidelines, WHO air quality limits, South African National Ambient Air Quality Standards (SANAAQS), and US EPA trace element reference levels. The mean PM2.5 level was 10 mu g/m3 (range: 1.1-29 mu g/m3), exceeding the WHO annual air quality limit (5 mu g/m3) but below SANAAQS (20 mu g/m3). PM2.5 posed health risks (hazard quotient > 1) across all age groups. Among 18 trace elements, Ca, Fe, K, S, and Si showed the highest levels (110-240 ng/m3). The excess cancer risk from Ni was 1.2 x 10-6. These findings underscore the need for targeted air quality controls to reduce PM2.5 and trace elements from dust and anthropogenic sources, to protect public health in Mabopane and similar areas.

Mounting evidence supports associations between air pollution and noise exposure and cardiovascular events; however, the relationships at low exposure levels and for stroke outcomes remain uncertain. The aim was to investigate the associations between environmental exposures over 1-year and 10-year periods and both stroke severity and stroke type in a registry-based cohort including people with stroke residing in a low-pollution area of Sweden. Patients with stroke admitted to the Sahlgrenska University Hospital from 2014 to 2019 were included. Stroke severity was assessed with the National Institutes of Health Stroke Scale and stroke types were ischemic and hemorrhagic. Annual residential environmental exposures (road traffic noise (L Aeq , 24h ), inhalable particulate matter (PM 10 ), and nitrogen oxides (NO x )) were assigned from high-resolution dispersion models to participants one year and for ten years prior to stroke, respectively. Of 4066 patients, 1965 (48.3%) were women. The mean (± SD) age was 73.6 (14.0) years. A total of 1563 (28%) had moderate to severe stroke, and 3603 (88.6%) had ischemic stroke. We did not find significant associations between environmental exposures (L Aeq,24h , NO x , PM 10 ) and stroke severity nor stroke type. The generally low levels of exposure and low variance of these environmental factors might explain the lack of observed associations.

Outdoor PM2.5 samples were collected for 34 months in Pretoria, South Africa from 18 April 2017 to 28 February 2020. The average total PM2.5 concentration was 23.2 ± 17.3 µg.m3 (0.69–139 µg.m−3), with the highest mean recorded during winter and the lowest during summer (p < 0.05). The sources were determined by means of cross referencing the US EPA PMF 5.0 program and the NOAA HYsplit model. The sources of the total PM2.5 were mining (33%), resuspended dust (24%), industry (15%), general exhaust (12%), vehicular emissions (12%) and biomass burning (4%). Sources of air pollutants are both ubiquitous and seasonal.

Traditional methods for measuring chemical exposure have challenges in terms of obtaining sufficient data; therefore, improved methods for better assessing occupational exposure are needed. One possible approach to mitigate these challenges is to use self-monitoring methods such as sensors, diaries, or biomarkers. In the present study, a self-monitored method for measuring soot exposure, which included real-time air monitoring, a work diary, and the collection of urine samples, was evaluated. To validate the method, exposure measurements during the workday and diary entries were compared with velocities calculated from GPS tracking and the expected polycyclic aromatic hydrocarbon (PAH) metabolite patterns in urine. The method was applied with chimney sweeps, an occupational group at a high risk of many severe health outcomes and for whom effective control measures for reducing exposure are needed. In the study, 20 chimney sweeps followed a self-monitoring protocol for 8 consecutive workdays. Personal exposure to soot was measured as black carbon (BC) using micro-aethalometers. A diary was used to record the work tasks performed, and urine samples were collected and analysed for PAH metabolites. From the expected 160 full day measurements, 146 (91%) BC measurements and 149 (93%) diaries were collected. From the expected 320 urine samples, 304 (95%) were collected. The tasks noted in the diaries overlapped with information obtained from the GPS tracking of the chimney sweeps, which covered 96% of the measurement time. The PAH metabolites in urine increased during the work week. Factors believed to have positively influenced the sample collection and task documentation were the highly motivated participants and the continuous presence of trained occupational hygiene professionals during the planning of the study and throughout the measurement stage, during which they were available to inform, instruct, and address questions. In conclusion, the self-monitored protocol used in this study with chimney sweeps is a valuable and valid method that can be used to collect larger numbers of samples. This is especially valuable for occupations in which the employees are working independently and the exposure is difficult to monitor with traditional occupational hygiene methods.

Outdoor PM2.5 was sampled in Pretoria, 18 April 2017 to 28 February 2020. A case-crossover epidemiology study was associated for increased PM2.5 and trace elements with increased hospital admissions for respiratory disorders (J00-J99). The results included a significant increase in hospital admissions, with total PM2.5 of 2.7% (95% CI: 0.6, 4.9) per 10 µg·m-3 increase. For the trace elements, Ca of 4.0% (95% CI: 1.4%-6.8%), Cl of 0.7% (95% CI: 0.0%-1.4%), Fe of 3.3% (95% CI: 0.5%-6.1%), K of 1.8% (95% CI: 0.2-3.5) and Si of 1.3% (95% CI: 0.1%-2.5%). When controlling for PM2.5, only Ca of 3.2% (95% CI: 0.3, 6.1) and within the 0-14 age group by 5.2% (95% CI: 1.5, 9.1). Controlling for a co-pollutant that is highly correlated with PM2.5 does reduce overestimation, but further studies should include deposition rates and parallel sampling analysis.

Background and aims Despite firm evidence for an association between long-term ambient air pollution exposure and cardiovascular morbidity and mortality, results from epidemiological studies on the association between air pollution exposure and atherosclerosis have not been consistent. We investigated associations between long-term low-level air pollution exposure and coronary atherosclerosis. Methods We performed a cross-sectional analysis in the large Swedish CArdioPulmonary bioImaging Study (SCAPIS, n = 30 154), a random general population sample. Concentrations of total and locally emitted particulate matter <2.5 mu m (PM2.5), <10 mu m (PM10), and nitrogen oxides (NOx) at the residential address were modelled using high-resolution dispersion models. We estimated associations between air pollution exposures and segment involvement score (SIS), coronary artery calcification score (CACS), number of non-calcified plaques (NCP), and number of significant stenoses, using ordinal regression models extensively adjusted for potential confounders. Results Median 10-year average PM2.5 exposure was 6.2 mu g/m(3) (range 3.5-13.4 mu g/m(3)). 51 % of participants were women and 51 % were never-smokers. None of the assessed pollutants were associated with a higher SIS or CACS. Exposure to PM2.5 was associated with NCP (adjusted OR 1.34, 95 % CI 1.13, 1.58, per 2.05 mu g/m(3)). Associations with significant stenoses were inconsistent. Conclusions In this large, middle-aged general population sample with low exposure levels, air pollution was not associated with measures of total burden of coronary atherosclerosis. However, PM2.5 appeared to be associated with a higher prevalence of non-calcified plaques. The results suggest that increased risk of early-stage atherosclerosis or rupture, but not increased total atherosclerotic burden, may be a pathway for long-term air pollution effects on cardiovascular disease.

Abstract Diesel exhaust exposure is a known carcinogen even at low levels of exposure. The new occupational exposure limit for diesel exhausts is based on the measurement of elemental carbon (EC) which went into effect at the beginning of 2023 in EU. The analysis of EC is not extremely expensive, but specialised instrument is needed for the analysis, which may not be accessible everywhere. An alternative method for measure diesel exhaust exposure is black carbon (BC) with an aethalometer, a real time monitoring instrument, making it possible to identify working tasks that are more prone to cause exposure. The EC measurement on the other hand gives an integrated amount, an average over the whole sampling time. There is a large overlap between what is BC and what is EC, so BC could be a good proxy for the EC exposure. The study we have conducted aims to investigate how well the exposure measurement of an aethalometer and measurement of EC correlate in different work environments. In the current study we have measured BC and EC in three types of environments, two occupational and one test chamber study. The two occupational environments studied were in mines and in a warehouse where diesel trucks were used to move wares. The results shows that BC and EC signals have good correlation, but that BC usually gives a higher average exposure over the day. This could be due to multitude of reasons, but one of them could be presence of other light absorbing particles.

Background:Available evidence suggests a link between exposure to transportation noise and an increased risk of obesity. We aimed to assess exposure-response functions for long-term residential exposure to road traffic, railway and aircraft noise, and markers of obesity.Methods:Our cross-sectional study is based on pooled data from 11 Nordic cohorts, including up to 162,639 individuals with either measured (69.2%) or self-reported obesity data. Residential exposure to transportation noise was estimated as a time-weighted average Lden 5 years before recruitment. Adjusted linear and logistic regression models were fitted to assess beta coefficients and odds ratios (OR) with 95% confidence intervals (CI) for body mass index, overweight, and obesity, as well as for waist circumference and central obesity. Furthermore, natural splines were fitted to assess the shape of the exposure-response functions.Results:For road traffic noise, the OR for obesity was 1.06 (95% CI = 1.03, 1.08) and for central obesity 1.03 (95% CI = 1.01, 1.05) per 10 dB Lden. Thresholds were observed at around 50-55 and 55-60 dB Lden, respectively, above which there was an approximate 10% risk increase per 10 dB Lden increment for both outcomes. However, linear associations only occurred in participants with measured obesity markers and were strongly influenced by the largest cohort. Similar risk estimates as for road traffic noise were found for railway noise, with no clear thresholds. For aircraft noise, results were uncertain due to the low number of exposed participants.Conclusion:Our results support an association between road traffic and railway noise and obesity.

Outdoor PM2.5 samples were collected for 34 months in Pretoria, South Africa from 18 April 2017 to 28 February 2020. The average total PM2.5 concentration was 23.2 +/- 17.3 mu g.m(3) (0.69-139 mu g.m(-3)), with the highest mean recorded during winter and the lowest during summer (p < 0.05). The sources were determined by means of cross referencing the US EPA PMF 5.0 program and the NOAA HYsplit model. The sources of the total PM2.5 were mining (33%), resuspended dust (24%), industry (15%), general exhaust (12%), vehicular emissions (12%) and biomass burning (4%). Sources of air pollutants are both ubiquitous and seasonal.Highlights center dot In central Pretoria, the largest contributing sources of PM2.5 are resuspended dust matrix and mining from surrounding areas;center dot A winter analysis was run where As, Se and Pb was included in the dataset, confirming biomass burning sources which were typically higher during the winter season; and center dot Air quality management policies should address both ubiquitous and seasonal sources.