Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m-3 in the North China Plain (NCP) and 23 µg m-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Recent Urban Issues Related to Particulate Matter in Ploiesti City, Romania

The present work aimed to assess the ambient levels of air pollution with particulate matter for both mass concentrations and number of particles for various fractions in Ploiesti city during the lockdown period determined by the COVID-19 pandemic (March–June 2020). The PM10 continuously monitored data was retrieved from four air quality automatic stations that are connected to the Romanian National Network for Monitoring Air Quality and located in the city. Because no other information was available for other more dangerous fractions, we used monitoring campaigns employing the Lighthouse 3016 IAQ particle counter near the locations of monitoring stations assessing size-segregated mass fraction concentrations (PM0.5, PM1, PM2.5, PM5, PM10, and TPM) and particle number concentration (differential Δ) range between 0.3 and 10 microns during the specified timeline between 8.00 and 11.00 a.m., which were considered the morning rush hours interval. Interpolation maps estimating the spatial distribution of the mass concentrations of various PM fractions and particle number concentration were drawn using the IDW algorithm in ArcGIS 10.8.2. Regarding the particle count of 0.5 microns during the lockdown, the smallest number was recorded when the restriction of citizens' movement was declared (24 March 2020), which was 5.8-times lower (17,301.3 particles/cm3) compared to a common day outside the lockdown period (100,047.3 particles/cm3). Similar results were observed for other particle sizes. Regarding the spatial distribution of the mass concentrations, the smaller fractions were higher in the middle of the city and west (PM0.5, PM1, and PM2.5) while the PM10 was more concentrated in the west. These are strongly related to traffic patterns. The analysis is useful to establish the impact of PM and the assessment of urban exposure and better air quality planning. Long-term exposure to PM in conjunction with other dangerous air pollutants in urban aerosols of Ploiesti can lead to potential adverse effects on the population, especially for residents located in the most impacted areas.

Role of the COVID-19 imposed lockdown in climate change

As the transmission of COVID-19 increases rapidly, the whole world adopted the lockdown activity with restriction of human mobility to prevent its spread. Everyone thinks of the COVID-19 negatively;however, it has some positive aspects too. Before COVID-19, the world was suffering by a high level of urban air pollution especially in the form of CO2, SO2, NO2 and particulate matter. During the COVID-19 pandemic, lockdown and limited human engagement with nature accompanied by social distance have proven to be beneficial for nature. As a result, significant reduction in environmental pollution and improvement in the quality of air, cleaner rivers, less noise pollution, undisturbed and calm wildlife was observed. Knowledge gained from the studies suggests that a substantial relationship exists between the contingency measures and environmental health. It is concluded that the COVID-19-induced lockdown has a positive impact on the global warming, a major issue of the 21st century.

Assessing lake water quality during COVID-19 era using geospatial techniques and artificial neural network model.

The present study evaluates the impact of the COVID-19 lockdown on the water quality of a tropical lake (East Kolkata Wetland or EKW, India) along with seasonal change using Landsat 8 and 9 images of the Google Earth Engine (GEE) cloud computing platform. The research focuses on detecting, monitoring, and predicting water quality in the EKW region using eight parameters-normalized suspended material index (NSMI), suspended particular matter (SPM), total phosphorus (TP), electrical conductivity (EC), chlorophyll-α, floating algae index (FAI), turbidity, Secchi disk depth (SDD), and two water quality indices such as Carlson tropic state index (CTSI) and entropy­weighted water quality index (EWQI). The results demonstrate that SPM, turbidity, EC, TP, and SDD improved while the FAI and chlorophyll-α increased during the lockdown period due to the stagnation of water as well as a reduction in industrial and anthropogenic pollution. Moreover, the prediction of EWQI using an artificial neural network indicates that the overall water quality will improve more if the lockdown period is sustained for another 3 years. The outcomes of the study will help the stakeholders develop effective regulations and strategies for the timely restoration of lake water quality.

Performance of Bayesian Model Averaging (BMA) for Short-Term Prediction of PM10 Concentration in the Peninsular Malaysia

In preparation for the Fourth Industrial Revolution (IR 4.0) in Malaysia, the government envisions a path to environmental sustainability and an improvement in air quality. Air quality measurements were initiated in different backgrounds including urban, suburban, industrial and rural to detect any significant changes in air quality parameters. Due to the dynamic nature of the weather, geographical location and anthropogenic sources, many uncertainties must be considered when dealing with air pollution data. In recent years, the Bayesian approach to fitting statistical models has gained more popularity due to its alternative modelling strategy that accounted for uncertainties for all air quality parameters. Therefore, this study aims to evaluate the performance of Bayesian Model Averaging (BMA) in predicting the next-day PM10 concentration in Peninsular Malaysia. A case study utilized seventeen years' worth of air quality monitoring data from nine (9) monitoring stations located in Peninsular Malaysia, using eight air quality parameters, i.e., PM10, NO2, SO2, CO, O3, temperature, relative humidity and wind speed. The performances of the next-day PM10 prediction were calculated using five models' performance evaluators, namely Coefficient of Determination (R2), Index of Agreement (IA), Kling-Gupta efficiency (KGE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The BMA models indicate that relative humidity, wind speed and PM10 contributed the most to the prediction model for the majority of stations with (R2 = 0.752 at Pasir Gudang monitoring station), (R2 = 0.749 at Larkin monitoring station), (R2 = 0.703 at Kota Bharu monitoring station), (R2 = 0.696 at Kangar monitoring station) and (R2 = 0.692 at Jerantut monitoring station), respectively. Furthermore, the BMA models demonstrated a good prediction model performance, with IA ranging from 0.84 to 0.91, R2 ranging from 0.64 to 0.75 and KGE ranging from 0.61 to 0.74 for all monitoring stations. According to the results of the investigation, BMA should be utilised in research and forecasting operations pertaining to environmental issues such as air pollution. From this study, BMA is recommended as one of the prediction tools for forecasting air pollution concentration, especially particulate matter level.

Comparative retrieval approaches for concentrated Suspended Particulate Matter (CSPM) detection in the Ganges using Sentinel-2 and Cloud Computing

In this paper, there are four distinct models utilized for the retrieval of CSPM from the Sentinel 2A/2B satellite imageries by using cloud computing techniques. In this study, a comparative analysis of different CSPM models was carried out at three different sites (Haridwar, Varanasi, and Hooghly). The study reveals that there are significant changes in CSPM in the Ganges in three different periods such as pre, during, and post-COVID. Noteworthy, fewer anthropogenic activities have generated important transformations in aquatic environments during the COVID. © 2023 IEEE.

Capturing Secchi disk depth by using Sentinel-2 MSI imagery in Jiaozhou Bay, China from 2017 to 2021

Water clarity is a key parameter for assessing changes of aquatic environment. Coastal waters are complex and variable, remote sensing of water clarity for it is often limited by low spatial resolution. The Sentinel-2 Multi-Spectral Instrument (MSI) imagery with a resolution of up to 10 m are employed to solve the problem from 2017 to 2021. Distribution and characteristics of Secchi disk depth (SDD) in Jiaozhou Bay (JZB) are analyzed. Subtle changes in localized small areas are discovered, and main factors affecting the changes are explored. Among natural factors, precipitation and wind play dominant roles in variation in SDD. Human activities have a significant influence on transparency, among which fishery farming has the greatest impact. This is clearly evidenced by the significant improvement of SDD in JZB due to the sharp decrease in human activities caused by coronavirus disease 2019 (COVID-19).Copyright © 2022 The Authors

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi‐Natural Experiment

In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID‐19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM10 (27%), PM2.5 (19%), NO2 (74%), SO2 (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21‐days lockdown is implemented, then a reduction of 42 µg m−3 in PM10, 23 µg m−3 in PM2.5, 14 µg m−3 in NO2, 2 µg m−3 in SO2, and 0.7 mg m−3 in CO can be achieved.

Evaluation of river water quality in a tropical South Sumatra wetland during COVID-19 pandemic period

The COVID-19 outbreak affected the world badly in this 21st century leading to the closure of all types of anthropogenic activities. It is declared that there was an environmental betterment in names of water quality and air quality during the COVID-19 period. In this study, we analyzed the improvement in water quality by evaluating the suspended particulate matter (SPM) using the remote sensing technique in a tropical South Sumatra wetland i.e., Musi River in Southern Sumatra, Indonesia. The SPM values were estimated from Landsat 8 images Level-2 product. A quantitative and spatial analyses of before (20th May 2019), during (22nd May 2020), and after COVID-19 (28th May 2022) periods were also calculated. Results revealed that the mean SPM values during COVID-19 period (4.56 mg/L) were lower than that before COVID-19 period (8.33 mg/L). Surprisingly, SPM showed an increase of 54% in SPM values after COVID-19 period, compared with during COVID-19 period. The role of human activities including industrial and domestic wastes during the restriction period was the main reason for alteration of pollution loads in the river. Outputs of this study can be used to arrange policies for the sustainable management of aquatic environments and water resources. © 2023 the Author(s), licensee AIMS Press.

Industrial Wastewater Discharge and Compliance Investigation for Environmentally Resilient Rwanda

While Rwanda is aiming at environmental pollution resilience and green growth, some industries are still discharging untreated effluent into the environment. This study gives a general overview of the compliance level of industrial effluent discharge in Rwanda and the linked negative environmental impacts. It comprises qualitative and quantitative analyses of data obtained from wastewater samples collected from five selected industries in Rwanda. The selected industries had previously been audited and monitored by the Rwanda Environment Management Authority (REMA), due to complains from neighboring residents. The study found that the effluent discharge from wastewater treatment plants (WWTP) for all concerned industries failed to comply with (i) oil and grease (O&G) national and international tolerable parameter limits or the (ii) fecal coliforms national standard. In addition, a compliance level of 66.7% was observed for key water quality monitoring parameters (pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), and heavy metals (i.e., lead (Pb), cadmium (Cd), and chromium (Cr)). Following these study findings, one industry was closed by the REMA for deliberately discharging untreated effluent into an adjacent river. This study recommends the adoption of the best available technology for effluent treatment, installation or renovation of existing WWTPs, and the relocation to industrial zones of industries adjacent to fragile environments.

Aviation contrail climate effects in the North Atlantic from 2016 to 2021

Around 5 % of anthropogenic radiative forcing (RF) is attributed to aviation CO2 and non-CO2 impacts. This paper quantifies aviation emissions and contrail climate forcing in the North Atlantic, one of the world's busiest air traffic corridors, over 5 years. Between 2016 and 2019, growth in CO2 (+3.13% yr-1) and nitrogen oxide emissions (+4.5 % yr-1) outpaced increases in flight distance (+3.05 % yr-1). Over the same period, the annual mean contrail cirrus net RF (204–280 mW m-2) showed significant inter-annual variability caused by variations in meteorology. Responses to COVID-19 caused significant reductions in flight distance travelled (-66%), CO2 emissions (-71%) and the contrail net RF (-66%) compared with the prior 1-year period. Around 12 % of all flights in this region cause 80 % of the annual contrail energy forcing, and the factors associated with strongly warming/cooling contrails include seasonal changes in meteorology and radiation, time of day, background cloud fields, and engine-specific non-volatile particulate matter (nvPM) emissions. Strongly warming contrails in this region are generally formed in wintertime, close to the tropopause, between 15:00 and 04:00 UTC, and above low-level clouds. The most strongly cooling contrails occur in the spring, in the upper troposphere, between 06:00 and 15:00 UTC, and without lower-level clouds. Uncertainty in the contrail cirrus net RF (216–238 mW m-2) arising from meteorology in 2019 is smaller than the inter-annual variability. The contrail RF estimates are most sensitive to the humidity fields, followed by nvPM emissions and aircraft mass assumptions. This longitudinal evaluation of aviation contrail impacts contributes a quantified understanding of inter-annual variability and informs strategies for contrail mitigation.

Impacts of Air Pollution and Dampness on Occupant Respiratory Health in Unplanned Houses: A Case Study of Bandung, Indonesia

This paper presents the results from field measurements and household surveys on the severity of indoor mold risk and its impact on respiratory health in a typical unplanned neighborhood of kampungs in Bandung, Indonesia. Mold risk was investigated using fungal risk detectors (n = 102), while air pollution levels were established with total suspended particulate (TSP) and particulate matter (PM2.5) (n = 38). The self-reported prevalence of respiratory diseases was obtained using a questionnaire form (ATS-DLD-78) (n = 599). The results showed that respiratory health problems were higher in the rainy season, particularly among children. Most houses suffered from severe mold risk, primarily due to extreme humid weather conditions, especially during rainy season (97%) where water leakage was prevalent (60%). In addition, the TSP and PM2.5 concentrations exceeded the WHO standards in most kampung houses, where around 58% of the houses recorded higher outdoor mean PM2.5 concentrations than indoors. Further, the path analysis showed that allergies followed by humidity rate and smell, which were affected by window-opening duration, directly impacted children’s respiratory health. Smoking behavior and building-related health problems, due to exposure to outdoor air pollution, affected the respiratory health of those aged 15 years old and over.

Assessment and Impacts of Air Pollution from Brick Kilns on Public Health in Northern Pakistan

Brick kilns add enormous quantities of organic pollutants to the air that can cause serious health issues, especially in developing countries;poor air quality is associated with community health problems, yet receives no attention in Northern Pakistan. The present study, therefore, assessed the chemical composition and investigated the impacts of air pollution from brick kilns on public health. A field-based investigation of air pollutants, i.e., PM1, PM2.5 and PM10, CO2, CO, NO, NO2, H2S, and NH3 using mobile scientific instruments was conducted in selected study area locations. Social surveys were conducted to investigate the impacts of air pollution on community health. The results reveal the highest concentrations of PM1, PM2.5, and PM10, i.e., 3377, 2305, and 3567.67 µg/m3, respectively, in specific locations. Particulate matter concentrations in sampling points exceeded the permissible limits of the Pakistan National Environmental Quality Standard and, therefore, may risk the local population’s health. The highest mean value of CO2 was 529 mg/L, and other parameters, such as CO, NO, NO2, H2S, and NH3 were within the normal range. The social survey’s findings reveal that particulate matter was directly associated with respiratory diseases such as asthma, which was reported in all age groups selected for sampling. The study concluded by implementing air pollution reduction measures in brick kiln industries to protect the environment and community health. In addition, the region’s environmental protection agency needs to play an active role in proper checking and integrated management to improve air quality and protect the community from air hazards.

PM10 variation, composition, and source analysis in Tuscany (Italy) following the COVID-19 lockdown restrictions

To control the spread of COVID-19, exceptional restrictive measures were taken in March 2020 that imposed a radical change on the lifestyle of millions of citizens around the world, albeit for a short period. The national lockdown, which lasted from 10 March to 18 May 2020 in Italy, was a unique opportunity to observe the variation in air quality in urban environments under conditions comprising almost total traffic restriction and a strong reduction in work activities. In this paper, the data from 17 urban monitoring sites in Tuscany are presented, and the PM and NO2 concentrations in the 2 months before the start of the lockdown and the 2 months after lockdown are compared with the corresponding months of the previous 3 years. The results show that the total loads of PM2.5 and PM10 (particulate matter with an aerodynamic diameter smaller than 2.5 and 10 µm, respectively) decreased, but they did not exhibit significant changes compared to previous years, whereas NO2 underwent a drastic reduction. For three of these sites, the chemical composition of the collected samples was measured using thermal–optical techniques, ion chromatography, and particle-induced X-ray emission analysis, and the application of multivariate positive matrix factorization analysis also allowed for PM10 source identification and apportionment. Using these analyses, it was possible to explain the low sensitivity of PM10 to the lockdown effects as being due to different, sometimes inverse, behaviors of the different sources that contribute to PM. The results clearly indicate a decline in pollution levels related to urban traffic and an increase in the concentration of sulfate for all sites during the lockdown period.

Urban Particulate Matter Hazard Mapping and Monitoring Site Selection in Nablus, Palestine

Few air pollution studies have been applied in the State of Palestine and all showed an increase in particulate matter concentrations above WHO guidelines. However, there is no clear methodology for selecting monitoring locations. In this study, a methodology based on GIS and locally calibrated low-cost sensors was tested. A GIS-based weighted overlay summation process for the potential sources of air pollution (factories, quarries, and traffic), taking into account the influence of altitude and climate, was used to obtain an air pollution hazard map for Nablus, Palestine. To test the methodology, eight locally calibrated PM sensors (AirUs) were deployed to measure PM2.5 concentrations for 55 days from 7 January to 2 March 2022. The results of the hazard map showed that 82% of Nablus is exposed to a high and medium risk of PM pollution. Sensors’ readings showed a good match between the hazard intensity and PM concentrations. It also shows an elevated PM2.5 concentrations above WHO guidelines in all areas. In summary, the overall average for PM2.5 in the Nablus was 48 µg/m3. This may indicate the effectiveness of mapping methodology and the use of low-cost, locally calibrated sensors in characterizing air quality status to identify the potential remediation options.

Spatialized Analysis of Air Pollution Complaints in Beijing Using the BERT+CRF Model

(1) Background: To better carry out air pollution control and to assist in accurate investigations of air pollution, in this study, we fully explore the spatial distribution characteristics of air pollution complaint results and provide guidance for air pollution control by combining regional air monitoring data. (2) Methods: By selecting the air pollution complaint information in Beijing from 2019 to 2020, in this study, we extract the names and addresses of complaint points, as well as the complaint times and types by adopting the BERT (bidirectional encoder representations from transformers) + CRF (conditional random field) model deep learning method. Moreover, through further filtering and processing of the complaint points’ address information, we achieve address matching and spatial positioning of the complaint points, and realize the regional spatial representation of air pollution complaints in Beijing in the form of a heat map. (3) Results: The experimental results are compared and analyzed with the ranking data of total suspended particulate (TSP) concentration of townships (streets) in Beijing during the same period, indicating that the key areas of air pollution complaints have a high correlation with the key polluted township (street) areas. The distribution of complaints and the types of complaints in each township (street) differ according to the population density in each township (street), the level of education, and economic activity. (4) Conclusions: The results of this study show that the public, as the intuitive perceiver of air pollution, is sensitive to the air pollution situation at a smaller spatial scale;furthermore, complaints can provide guidance and reference for the direction of air pollution control and law enforcement investigations when coupled with geographical features and economic status.

Environmental Geochemistry and Positive Impact of Covid-19 Pandemic with Special Emphasis to Coal Mining Industry: An Overview

In the present situation, Covid-19 is considered to be an unbeaten global pandemic. In every single fleeting moment, this SARS-CoV-2 (coronavirus-2) causes greater damage to our life including the physical world including drastic imbalance of the whole economic condition of any country. The lockdown governed in two consecutive years (2020 and 2021) in the world to control the spreading of the virus poses an undue threat to the industrial sectors including the coal mining sectors that determine the economic growth of the country. With these negative impacts of coronavirus-2 in our life, this present review aims to explore some of the positive influences of the Covid-19 pandemic through the restoration of the environmental system which are otherwise not possible. This quantitative review finds that spreading of the Covid-19 pandemic indirectly improves the air and water quality by reducing the number of vehicles, reduces the CO2, NOx, particulate matter, and other polluting gases emission from coal-based power plants through periodical lockdown in the country. Moreover, the lockdown implemented to minimise the spreading of the Covid-19 significantly reduces the coal dust production from the mining and transportation of coal that indirectly reduces environmental pollution.

A model for simultaneous evaluation of NO2, O3, and PM10 pollution in urban and rural areas: handling incomplete data sets with multivariate curve resolution analysis

A powerful methodology, based on the multivariate curve resolution alternating least squares (MCR-ALS) method with quadrilinearity constraints, is proposed to handle complex and incomplete four-way atmospheric data sets, providing concise results that are easy to interpret. Changes in air quality by nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM10) in eight sampling stations located in the Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown period (2020) with respect to previous years (2018 and 2019), are investigated using such methodology. The MCR-ALS simultaneous analysis of the three contaminants among the eight stations and for the 3 years allows the evaluation of potential correlations among the pollutants, even when having missing data blocks. Correlated profiles are shown by NO2 and PM10 due to similar pollution sources (traffic and industry), evidencing a decrease in 2019 and 2020 due to traffic restriction policies and the COVID-19 lockdown period, especially noticeable in the most transited urban areas (i.e., Vall d'Hebron, Granollers and Gràcia). The O3 evidences an opposed interannual trend, showing higher amounts in 2019 and 2020 with respect to 2018 due to the decreased titration effect, more significant in rural areas (Begur) and in the control site (Obserbatori Fabra).

The dynamics of the first wave of COVID-19 on environment and wildlife– a boon or a bane?

Even though COVID-19 has drastically weighed upon the humankind, still there is a "silver lining" to see in this dark time. Amidst of this pandemic, most of the human activities were restricted to break the chain of infection which resulted the remarkable change in nature. It has been reported that due to halt in air travel, reduction in the use of fossil fuels, way less functioning of vehicles, shutdown of industries has complied the change in air pollution levels and also change in river water quality. Reports also showed the reduction in particulate matter (PM 2.5 and PM 10), greenhouse gases emissions, massive improvement in the Air quality index (AQI), reduction in the NOX and SOX's levelhas clearly stipulated that nature has got it's time to "revive". Even the global carbon emission has reported to reduced reluctantly which is expected to be the biggest such drop since World War II. Despite conducting water-cleansing projects and spending a lot of money, the situation of the water bodies were far better now during first lockdown. Moreover, migration and breeding of the birds and animals have been reported to be restored to normal pattern due to depletion in man-animal conflict. Apart from the positive, negative impacts on the nature are also being experienced. Our review work is highlighting such impacts witnessed during the first wave of COVID-19, like, the significant improvement in air and water quality, reduction in environmental noise, therefore an in turn cleaner and quieter habitat for the wildlife to mate and also to quench their curiosities by their surprising excursions;but there are also some negative aspects as well, like reduction in recycling and the increase in waste, increased poaching and even lone shuttering of zoo animals.

Absorption enhancement of black carbon particles in a Mediterranean city and countryside: effect of particulate matter chemistry, ageing and trend analysis

Black carbon (BC) is recognized as the most important warming agent among atmospheric aerosol particles. The absorption efficiency of pure BC is rather well-known, nevertheless the mixing of BC with other aerosol particles can enhance the BC light absorption efficiency, thus directly affecting Earth's radiative balance. The effects on climate of the BC absorption enhancement due to the mixing with these aerosols are not yet well constrained because these effects depend on the availability of material for mixing with BC, thus creating regional variations.Here we present the mass absorption cross-section (MAC) and absorption enhancement of BC particles (Eabs), at different wavelengths (from 370 to 880 nm for online measurements and at 637 nm for offline measurements) measured at two sites in the western Mediterranean, namely Barcelona (BCN;urban background) and Montseny (MSY;regional background). The Eabs values ranged between 1.24 and 1.51 at the urban station, depending on the season and wavelength used as well as on the pure BC MAC used as a reference. The largest contribution to Eabs was due to the internal mixing of BC particles with other aerosol compounds, on average between a 91 % and a 100 % at 370 and 880 nm, respectively. Additionally, 14.5 % and 4.6 % of the total enhancement at the short ultraviolet (UV) wavelength (370 nm) was due to externally mixed brown carbon (BrC) particles during the cold and the warm period, respectively. On average, at the MSY station, a higher Eabs value was observed (1.83 at 637 nm) compared to BCN (1.37 at 637 nm), which was associated with the higher fraction of organic aerosols (OA) available for BC coating at the regional station, as denoted by the higher organic carbon to elemental carbon (OC:EC) ratio observed at MSY compared to BCN. At both BCN and MSY, Eabs showed an exponential increase with the amount of non-refractory (NR) material available for coating (RNR-PM). The Eabs at 637 nm at the MSY regional station reached values up to 3 during episodes with high RNR-PM, whereas in BCN, Eabs kept values lower than 2 due to the lower relative amount of coating materials measured at BCN compared to MSY. The main sources of OA influencing Eabs throughout the year were hydrocarbon OA (HOA) and cooking-related OA (COA), i.e. primary OA (POA) from traffic and cooking emissions, respectively, at both 370 and 880 nm. At the short UV wavelength (370 nm), a strong contribution to Eabs from biomass burning OA (BBOA) and less oxidized oxygenated OA (LO-OOA) sources was observed in the colder period. Moreover, we found an increase of Eabs with the ageing state of the particles, especially during the colder period. This increase of Eabs with particle ageing was associated with a larger relative amount of secondary OA (SOA) compared to POA. The availability of a long dataset at both stations from offline measurements enabled a decade-long trend analysis of Eabs at 637 nm, that showed statistically significant (s.s.) positive trends of Eabs during the warmer months at the MSY station. This s.s. positive trend in MSY mirrored the observed increase of the OC:EC ratio over time. Moreover, in BCN during the COVID-19 lockdown period in spring 2020 we observed a sharp increase of Eabs due to the observed sharp increase of the OC:EC ratio. Our results show similar values of Eabs to those found in the literature for similar background stations.