Air Quality Management Policies Research Articles

SHERPA-Cloud: An open-source online model to simulate air quality management policies in Europe

In this manuscript we present the SHERPA-Cloud online simplified air quality model, which is an evolution of the previous offline SHERPA model. SHERPA-cloud is a meta-model of a full Chemical Transport Model, and can be used to screen how policies would impact air quality. The main advantages of SHERPA-cloud (in comparison to the previous model version) are its speed (5 time faster than the offline version), its accessibility (permanent online availability) and its easier and more cost-effective maintenance (automatic updates can be shared more easily, and tool developments are facilitated). From the IT infrastructure and technologies points of view, the SHERPA-Cloud is based on an in-house cloud system called BDAP (Big Data Analytic Platform) which provides a ’JupyterLab’ service and tools to create dashboards using ’Voilà’ technology. SHERPA-Cloud is a useful easy-to-use tool in the hands of policy makers, citizens, NGOs and industries, that allows for interactive and participative policy developments. Indeed, it allows to quickly quantify changes in air quality resulting from the implementation of emission reduction strategies, in terms of both geographical or sectoral policies.

Long-term (1993–2018) particulate polycyclic aromatic hydrocarbons (PAHs) concentration trend in the atmosphere of Seoul: Changes in major sources and health effects

This study assessed the long-term concentration trend and profiles of twelve polycyclic aromatic hydrocarbons (PAHs) occurring as airborne particulate matter in Seoul, Republic of Korea (Korea) between 1993 and 2018 to evaluate the human health effect and the effectiveness of air quality management policies. Total PAHs (∑PAHs of 12 compounds), benzo [a]pyrene (BaP), and BaP toxic equivalent (BaPTEQ) concentrations increased from 1993 to 1999 but decreased thereafter. Moreover, the BaP concentration has remained below 1 ng/m3 since 2010–2011. Benzo [b+k]fluoranthene (B [b+k]F) accounted for the largest ∑PAHs fraction (approximately 24%) for the entire period. Based on the PAH profiles, as well as the Principal Component Analysis (PCA) results and diagnostic ratio analysis, vehicular emissions and coal combustion were identified as major sources of the PAHs in Seoul. Additionally, contribution of vehicular emissions increased from 2002 to 2003 to 2018, whereas that of solid fuel combustion decreased in the same period. PAH levels increased 8-fold in winter compared to summer mainly due to increases in local and regional emissions. The implementation of policies to regulate the use of solid fuels and vehicular emissions in Korea effectively reduced Elemental Carbon (EC) and PAH emissions, as demonstrated by CO, EC, and PAHs reductions and a good correlation between EC and PAHs. Moreover, aggressive air quality management policies in China have also contributed to decreasing PAH concentration trend in Seoul. Following the incremental lifetime cancer risk (ILCR) estimations method for 8 different population groups, males in the 0–1 age group was the only group still at potential risk of PAH inhalation in 2018, while other groups have been in the acceptable risk since 2012–2013.

Quantifying the Light-Absorption Properties and Molecular Composition of Brown Carbon Aerosol from Sub-Saharan African Biomass Combustion.

Sub-Saharan Africa is a hotspot for biomass burning (BB)-derived carbonaceous aerosols, including light-absorbing organic (brown) carbon (BrC). However, the chemically complex nature of BrC in BB aerosols from this region is not fully understood. We generated smoke in a chamber through smoldering combustion of common sub-Saharan African biomass fuels (hardwoods, cow dung, savanna grass, and leaves). We quantified aethalometer-based, real-time light-absorption properties of BrC-containing organic-rich BB aerosols, accounting for variations in wavelength, fuel type, relative humidity, and photochemical aging conditions. In filter samples collected from the chamber and Botswana in the winter, we identified 182 BrC species, classified into lignin pyrolysis products, nitroaromatics, coumarins, stilbenes, and flavonoids. Using an extensive set of standards, we determined species-specific mass and emission factors. Our analysis revealed a linear relationship between the combined BrC species contribution to chamber-measured BB aerosol mass (0.4-14%) and the mass-absorption cross-section at 370 nm (0.2-2.2 m2 g-1). Hierarchical clustering resolved key molecular-level components from the BrC matrix, with photochemically aged emissions from leaf and cow-dung burning showing BrC fingerprints similar to those found in Botswana aerosols. These quantitative findings could potentially help refine climate model predictions, aid in source apportionment, and inform effective air quality management policies for human health and the global climate.

Spatiotemporal patterns of surface ozone exposure inequality in China.

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1km × 1km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118μg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7μg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Identification of places with deteriorated air quality in city of Žilina in relation to road transport

The aim of the research is to identify places with deteriorated air quality in the selected city. After an analytical analysis of the data, it is possible to propose steps that can be used to actively contribute to the reduction of air pollution, especially due to road traffic. Places where deteriorated air quality was identified were identified on the basis of practical measurements. Given that the measurement route was designed in a built-up area of the city with a large number of pedestrians, the research was primarily focused on the identification of particulate matters (PM) and the concentration of carbon monoxide CO. The measurements were performed repeatedly on a pre-defined route. The measurements were carried out repeatedly during the morning rush hour when traffic was congested on the roads. Based on the processing and evaluation of the measurements, the sections where increased values of individual emissions were recorded were determined. In this way, it is possible to precisely identify places where air quality deteriorates. The research conclusions provide support for planning the optimization of air quality management policies towards the creation of sustainable cities. The research results present the possibilities of identifying problematic sections from the point of view of emissions production. Critical places with regard to the production of emissions can be connected to places where a permanently increased movement of vehicles is observed.

The potential impact of policies and structural interventions in reducing cardiovascular disease and mortality: a systematic review of simulation-based studies.

The aim of the study was to investigate the potential effect of different structural interventions for preventing cardiovascular disease. Medline and EMBASE were searched for peer-reviewed simulation-based studies of structural interventions for prevention of cardiovascular disease. We performed a systematic narrative synthesis. A total of 54 studies met the inclusion criteria. Diet, nutrition, tobacco and alcohol control and other programmes are among the policy simulation models explored. Food tax and subsidies, healthy food and lifestyles policies, palm oil tax, processed meat tax, reduction in ultra-processed foods, supplementary nutrition assistance programmes, stricter food policy and subsidised community-supported agriculture were among the diet and nutrition initiatives. Initiatives to reduce tobacco and alcohol use included a smoking ban, a national tobacco control initiative and a tax on alcohol. Others included the NHS Health Check, WHO 25 × 25 and air quality management policy. There is significant heterogeneity in simulation models, making comparisons of output data impossible. While policy interventions typically include a variety of strategies, none of the models considered possible interrelationships between multiple policies or potential interactions. Research that investigates dose-response interactions between numerous modifications as well as longer-term clinical outcomes can help us better understand the potential impact of policy-level interventions. The reviewed studies underscore the potential of structural interventions in addressing cardiovascular diseases. Notably, interventions in areas such as diet, tobacco, and alcohol control demonstrate a prospective decrease in cardiovascular incidents. However, to realize the full potential of such interventions, there is a pressing need for models that consider the interplay and cumulative impacts of multiple policies. Rigorous research into holistic and interconnected interventions will pave the way for more effective policy strategies in the future. The study is registered as PROSPERO CRD42019154836. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 17/148/05.

Preliminary Research to Support Air Quality Management Policies for Basic Local Governments in Gyeonggi-do

Preliminary Research to Support Air Quality Management Policies for Basic Local Governments in Gyeonggi-do

Estimating annual GHG and particulate matter emissions from rural and forest fires based on an integrated modelling approach

Rural and forest fires represent one of the most significant sources of emissions in the atmosphere of trace gases and aerosol particles, which significantly impact carbon budget, air quality, and human health. This paper aims to illustrate an integrated modelling approach combining spatial and non-spatial inputs to provide and enhance the estimation of GHG and particulate matter emissions from surface fires using Italy as a case study over the period 2007–2017. Three main improvements characterize the approach proposed in this work: (i) the collection and development of comprehensive and accurate data inputs related to burned area; (ii) the use of the most recent data on fuel type and load; and (iii) the modelling application to estimate fuel moisture, burning efficiency, and fuel consumption considering meteorological factors and combustion phases. On average, Italy's GHG and particulate matter emissions were 2621 Gg yr−1, ranging from a minimum of 772 Gg yr−1 in 2013 to a maximum of 7020 Gg yr−1 in 2007. Emissions from fire disturbances in broadleaf forests, shrublands, and agricultural fuel types account for about 76 % of the total. Results were compared with global and national inventories and showed good agreement, especially considering CO2 and particulate matter. The approach of this study added confidence in emission estimates, and the results can be utilized in decision support systems to address air quality management and fire impact mitigation policies.

Impact of agricultural activity on PM2.5 and its compositions in elementary schools near corn and rice farms

Agricultural activity is an important source of particulate matter <2.5 μm in size (PM2.5) in rural areas. In Taiwan, many elementary schools are surrounded by farms, and studies investigating the impact of agricultural activity on air quality in schools are required. We collected PM2.5 samples from the classrooms of elementary schools near corn and rice farms during the crop cultivation stages and analyzed their concentrations and compositions to investigate whether agricultural activity affects the schools' air quality. We found that the average ratio of PM2.5/PM10 (<10 μm in particle size) was <0.6 in the school near the corn farm, and that the indoor PM2.5/PM10 ratio was significantly associated (r = 0.93, p < 0.05) with the outdoor ratio. Moreover, the potassium (K) concentration in the school near the corn farm (189.2 ± 119 ng/m3) was higher than that near the rice farm (140.9 ± 116.0 ng/m3). There were higher concentrations of K and crustal elements, and a greater crustal elements/heavy metals ratio, in the school near the corn farm during the sowing and soil covering stages than during other cultivation stages. Positive matrix factorization (PMF) results indicate that agricultural activity was a predominant contributor of PM2.5 in the schools near corn and rice farms, however, PM2.5 from industrial and traffic emissions also affected schools' air quality. In summary, agricultural activity influenced the air quality of schools, especially near the corn farm. Governments should develop air quality management policies to reduce the risk of children suffering exposure to high particle concentrations in these schools and further suggest that the impact of industrial and traffic emissions on air quality also requires attention.

Using Explainable Machine Learning to Interpret the Effects of Policies on Air Pollution: COVID-19 Lockdown in London.

Activity changes during the COVID-19 lockdown present an opportunity to understand the effects that prospective emission control and air quality management policies might have on reducing air pollution. Using a regression discontinuity design for causal analysis, we show that the first UK national lockdown led to unprecedented decreases in road traffic, by up to 65%, yet incommensurate and heterogeneous responses in air pollution in London. At different locations, changes in air pollution attributable to the lockdown ranged from -50% to 0% for nitrogen dioxide (NO2), 0% to +4% for ozone (O3), and -5% to +0% for particulate matter with an aerodynamic diameter less than 10 μm (PM10), and there was no response for PM2.5. Using explainable machine learning to interpret the outputs of a predictive model, we show that the degree to which NO2 pollution was reduced in an area was correlated with spatial features (including road freight traffic and proximity to a major airport and the city center), and that existing inequalities in air pollution exposure were exacerbated: pollution reductions were greater in places with more affluent residents and better access to public transport services.

Development of point sampling technology for identifying high-emitting vehicles in narrow and deep street canyons

Side road measurements of fine particle (FP) concentrations were performed in two narrow and deep street canyons in the historic center of Naples using point sampling technology (PS). The FP concentration in the range of 20–103 nm was measured using a condensation particle number counter (CPC) with a 1 Hz frequency. Video recording was used to detect passing vehicles classified into three categories: motorcycles, cars, and light-duty vehicles. The two monitored streets were adjacent, with similar geometrics and orientation but different high- and low-traffic levels. FP concentration time series data were processed to identify concentration peaks generated by the exhausts of passing vehicles. A sensitivity analysis study was carried out to determine how data processing parameters could affect high-emitting vehicle (high emitter) identification. Once the optimum parameters were defined, the contribution of high emitters exhaust emissions to local air quality was assessed. The results showed that PS technology offered viable opportunities for application in narrow street canyons where deploying more common crossroad and top-down monitoring can be troublesome. However, some issues remain to be solved to accurately identify high emitterss in high-traffic cases. PS technology can be useful for developing effective air quality management policies in historical centres.

Airborne fine particles drive H1N1 viruses deep into the lower respiratory tract and distant organs.

Mounting data suggest that environmental pollution due to airborne fine particles (AFPs) increases the occurrence and severity of respiratory virus infection in humans. However, it is unclear whether and how interactions with AFPs alter viral infection and distribution. We report synergetic effects between various AFPs and the H1N1 virus, regulated by physicochemical properties of the AFPs. Unlike infection caused by virus alone, AFPs facilitated the internalization of virus through a receptor-independent pathway. Moreover, AFPs promoted the budding and dispersal of progeny virions, likely mediated by lipid rafts in the host plasma membrane. Infected animal models demonstrated that AFPs favored penetration of the H1N1 virus into the distal lung, and its translocation into extrapulmonary organs including the liver, spleen, and kidney, thus causing severe local and systemic disorders. Our findings revealed a key role of AFPs in driving viral infection throughout the respiratory tract and beyond. These insights entail stronger air quality management and air pollution reduction policies.

Prediction of the air quality index of Hefei based on an improved ARIMA model

&lt;abstract&gt;&lt;p&gt;With the rapid development of the economy, the air quality is facing increasingly severe pollution challenges. The air quality is related to public health and the sustainable development of the environment of China. In this paper, we first investigate the changes in the monthly air quality index data of Hefei from 2014 to 2020. Second, we analyze whether the Spring Festival factors lead to the deterioration of the air quality index according to the time sequence. Third, we construct an improved model to predict the air quality index of Hefei. There are three primary discoveries: (1) The air quality index of Hefei has obvious periodicity and a trend of descent. (2) The influencing factors of Spring Festival have no significant effect on the air quality index series. (3) The air quality index of Hefei will maintain a fluctuating and descending trend for a period of time. Finally, some recommendations for the air quality management policy in Hefei are presented based on the obtained results.&lt;/p&gt;&lt;/abstract&gt;

Characterisation of ambient air quality over two urban sites on the South African Highveld

Air pollution is an environmental-health challenge that many developing and developed countries are struggling to deal with. The purpose of our study was to characterise the ambient air quality during the year 2019–2020 over two urban sites of DiepKloof and Vanderbijilpark which are located on the South African Highveld. The study characterised PM10, PM2.5, SO2, NO2 and O3. Findings were that PM10, PM2.5, SO2 and NO2 ambient concentrations predominantly peaked during the winter season in June, July and August with mean concentrations of 48.6 µg/m3, 29.2 µg/m3, 38.6 µg/m3 and 12.6 µg/m3, respectively for the DiepKloof site while for the Vanderbijilpark site, winter mean for PM10, PM2.5 and SO2 were recorded at 124 µg/m3, 50.7 µg/m3 and 22.1 µg/m3, respectively. The average daily pollutant concentrations of the majority of pollutants were elevated above the WHO air quality guideline limits. Analysis of variance showed the seasonal variations had a significant (all p-values less than 0.01) effect on the variability of pollutant concentrations in both sites. The study attributes these elevated ambient pollutant levels to industrial, domestic and vehicular emission sources that are scattered over the South African Highveld. The study also highlighted the impact of the first lockdown period in South Africa indicating that the first three-week lockdown had a significant (p-values less than 0.001) impact on the variability of pollutant concentrations in both Diep Kloof and Vanderbijlpark. The study also established that pollutant concentrations were more significantly affected by wind direction in the more industrialized Vanderbijlpark than in Diep Kloof. The study contributes towards air quality monitoring and management policy formulation both in South Africa and other African countries. Furthermore, the study contributes towards the academic body of knowledge. To curtail pollutant emissions governments have several options including tightening the air quality regulatory frameworks as well as establishing and supporting community-based air quality advocates. Air quality advocates can act as a conduit in raising general public awareness regarding the impact of air pollution on human health.

Sources of surface O3 in the UK: tagging O3 within WRF-Chem

Abstract. Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

Quantifying international and interstate contributions to primary ambient PM2.5 and PM10 in a complex metropolitan atmosphere

We quantify the contributions of long-range and regionally transported aerosols to ambient primary PM2.5 and PM10 in a representative United States industrialized/urban atmosphere via detailed elemental analysis and chemical mass balance (CMB) modeling after identifying their presence using a variety of publicly available satellite data/information, software products, and synoptic-scale aerosol models. A year-long study in Houston, Texas identified North African dust as the principal long-range global source of primary particulate matter (PM). CMB estimated transatlantic dust from the Sahara-Sahel region to be dominant in the summer months contributing an average of 3.5 μg m−3 to PM2.5 and 7.9 μg m−3 to PM10 during May–August, i.e., the active Saharan dust season. Biomass burning was the chief source of regionally transported PM impacting air quality on different occasions throughout the year depending on the fire location. Four major biomass combustion events affecting air quality in Texas were calculated to contribute an average of 1.3 μg m−3 to PM2.5 and 1.4 μg m−3 to PM10 in corresponding samples whose origins were tracked to Canada, southeastern states of USA, and Central America using fire maps, HYSPLIT back trajectories, and the Navy Aerosol Analysis and Prediction System global aerosol model. Elemental concentrations and signature ratios revealed significant mixing of potassium, rare earth metals, and vanadium from proximal and distal crustal (natural) sources with anthropogenically emitted PM. This demonstrates the need to isolate the non-mineral components of these metals to employ them as tracers for primary PM emitted by biomass burning, petroleum refineries, and oil combustion. Transboundary contributions to primary PM2.5 were 1.5 μg m−3 and 3.1 μg m−3 to PM10 adding 16% to annual average mass concentration of both size fractions demonstrating that local sources were primarily responsible for ambient air quality with non-trivial contributions from international and interstate sources. Rigorously identifying and quantifying aerosol sources assists in improving air quality management policies designed to protect public health and comply with ever-decreasing federal PM standards that allow state agencies to exclude contributions that are not reasonably controllable or preventable from regulatory decisions and actions.

Air pollution during COVID-19 pandemic: Exploration in the Bulgarian city of Stara Zagora using interrupted time series ARMA model

The COVID-19 global pandemic has likely affected air quality due to extreme changes in human behavior. The aim of this paper is to explore the consequence of the COVID-19 pandemic on the air quality improvement in the Bulgarian city of Stara Zagora using Interrupted Time Series ARMA Model. After adjusting by meteorology and Sunday effect, the results confirm positive and significant effect immediately after the announcement of COVID-19 pandemic in Bulgaria and negative and significant trend in the levels for PM[Formula: see text] and O3. For the remaining CO and NO series of data, the estimate of the time series slope, i.e. the expected change in the concentration associated with a time unit increase is positive and significant. The temporal dynamics for each time series are reported by the ARMA coefficients: an ARMA(2,3) structure is estimated for O3 and NO, and an ARMA(1,1) is the best choice for CO while AR(5) for PM[Formula: see text]. Understanding how air pollution is affected during COVID-19 pandemic will contribute to future air quality management policies and human health.

Estimation of health impact using AirQ+ model attributed to surface ozone in sub-regions of Surat city, India

Introduction: Deteriorated air quality in nation like India contributes to the health burden. The AirQ+ is used to estimate short-term and long-term health impact attributable to surface Ozone (O3) in Surat city. Average hourly ozone concentration data and other criteria pollutants retrieved from January 2018 to December 2019 from two monitoring stations (Limbayat and Varachha).&#x0D; Materials and methods: In this study, the Respiratory Mortality (RM), Cardiovascular Mortality (CM), Total Mortality (TM), Hospital Admissions with Cardiovascular Disease (HACVD), and Hospital Admissions with Respiratory Disease (HARD), as well as Respiratory Mortality-Long-Term (LT-RM) were quantified. Baseline Incidence (BI) data were obtained from literature and Relative Risk (RR) values were referred from World Health Organization (WHO). An annual Sum of Maximum 8 h Ozone means over 35 ppb (SOMO35), 70 µg/m3, used as a predictor of potential long-term health effects.&#x0D; Results: More ozone concentration were observed in winter and pre-monsoon than concentration formed in southwest monsoon and post-monsoon seasons.The average of O3 concentration for Limbayat are 71.61 (±0.39) µg/m3 and 29.76 (±1.86) µg/m3 and for Varachha are 61.17 9 (±6.15) µg/m3, 11.32 (±1.35) µg/m3 during 2018 and 2019, respectively and the obtained cumulative number of cases of death are estimated 136, 45, 172 and 18 persons respectively. Total hospital admission due to cardiovascular and respiratory diseases are found 435, 134, 552 and 58 at Limbayat and Varachha during 2018 and 2019. LT- RM is attributed to ozone concentration having the most significant value, 6.8% and 4.62% at Limbayat and Varachha in 2018.&#x0D; Conclusion: More hospital admissions are found than mortality rates using AirQ+ tool. It can be used to estimate public health in context of mortality and morbidity rates which helps to develop air quality management programs and policy makers to reduce the impact of air pollution on health.

Carbonaceous aerosols in Lvliang, China: seasonal variation, spatial distribution and source apportionment

Environmental context Lvliang, one of the main cities on the Fenwei Plain, is a key atmospheric pollution prevention area in China. Identification of sources of aerosols is essential to improving environmental air quality in this region. The quantitative source apportionment of carbonaceous aerosols performed in this study provides a better understanding of their sources and implications for climate and air-quality management policies in the Fenwei plain. Rationale Organic carbon (OC) and elemental carbon (EC) are major components of fine particulate matter (PM2.5), and they are of concern due to their significant impacts on human health and climate. Methodology PM2.5 samples were collected daily during four consecutive seasons from 2018 to 2019. This paper highlights the seasonal variations, sources and transport characteristics of carbonaceous aerosol in Lvliang, China. Results The OC and EC concentrations exhibited strong seasonal variations, with the highest in winter, mainly due to high pollution caused by winter heating in northern cities, and secondary OC (SOC) contribution. The average OC/EC ratio (1.72) in Lvliang was lower than those in most regions in China, further indicating that this region was greatly affected by primary source emissions. The highest SOC/OC ratio in summer (25.3%) was due to the positive correlation between SOC and temperature. Through the positive matrix factorisation (PMF) model, four sources of carbonaceous aerosols were identified: vehicle emissions (31.26%), coal combustion (30.83%), biomass combustion (24.36%) and dust emissions (13.55%). Potential source contribution function (PSCF) results indicated that in addition to the impact of local emissions, coal emissions from Ningxia and Shaanxi, motor vehicle emissions and biomass from Inner Mongolia and Ningxia and dust from Shaanxi and Henan Provinces were the major contributors to pollution. Discussion These data provide key information for formulating emission reduction policies and improving air quality on the Fenwei Plain and highlights the urgent need for inter-regional prevention and control measures for the cities in Lvliang.

Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes.

La Oroya is a city in the Peruvian Andes that has suffered a serious deterioration in its air quality, especially due to the high rate of sulfur dioxide (SO2) emissions, which underlines the importance of knowing its sources of contamination and variation over the years. In this sense, this study aimed to evaluate the immission levels and determine the sources of SO2 contamination in La Oroya. This analysis was performed using the hourly concentration data of SO2, and meteorological variables (wind speed and direction), which were analyzed for a period of three years (2018–2020). Graphs of time series, wind and pollutant roses, bivariate polar graphs, clustering k-means, nonparametric statistical tests, and the application of the conditional bivariate probability function were performed to analyze the data and identify the emission sources. The mean concentration of SO2 was 264.2 μg m−3 for the study period, where 55.66 and 2.37% of the evaluated days exceeded the guideline values recommended by the World Health Organization and the Peruvian Environmental Quality Standard for air for 24 h, respectively. The results showed a defined pattern for the daily and monthly variations, with peaks in the morning hours (0900–1000 h LT) and at the end of the year (December), respectively. The main sources of SO2 emissions identified were light and heavy vehicles that travel through the Central Highway, the La Oroya Metallurgical Complex, the transit of vehicles within the city, and the diesel–electric locomotives that provide cargo transportation services and tourism passenger transportation. The article attempts to contribute to the development of adequate air quality management policies.