Transport Of Pollutants Research Articles

Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes

Abstract. Super-resolution atmospheric modelling can be used to interpret and optimize environmental observations during top-down emission rate retrieval campaigns (e.g. aircraft-based) by providing complementary data that closely correspond to real-world atmospheric pollution transport and dispersion conditions. For this work, super-resolution model simulations with large-eddy-simulation sub-grid-scale parameterization were developed and implemented using WRF-ARW (Weather Research and Forecasting - Advanced Research WRF). We demonstrate a series of best practices for improved (realistic) modelling of atmospheric pollutant dispersion at super-resolutions. These include careful considerations for grid quality over complex terrain, sub-grid turbulence parameterization at the scale of large eddies, and ensuring local and global tracer mass conservation. The study objective was to resolve small dynamical processes inclusive of spatio-temporal scales of high-speed (e.g. 100 m s−1) airborne measurements. This was achieved by downscaling of reanalysis data from 31.25 km to 50 m through multi-domain model nesting in the horizontal and grid-refining in the vertical. Further, WRF dynamical-solver source code was modified to simulate the release of passive tracers within the finest-resolution domain. Different meteorological case studies and several tracer source emission scenarios were considered. Model-generated fields were evaluated against observational data (surface monitoring network and aircraft campaign data) and also in terms of tracer mass conservation. Results indicated agreement between modelled and observed values within 5 ∘C for temperature, 1 %–25 % for relative humidity, and 1–2 standard deviations for wind fields. Model performance in terms of (global and local) tracer mass conservation was within 2 % to 5 % of model input emissions. We found that, to ensure mass conservation within the modelling domain, tracers should be released on a regular-resolution grid (vertical and horizontal). Further, using our super-resolution modelling products, we investigated emission rate estimations based on flux calculation and mass-balancing. Our results indicate that retrievals under weak advection conditions (horizontal wind speeds < 5 m s−1) are not reliable due to weak correlation between the source emission rate and the downwind tracer mass flux. In this work we demonstrate the development of accurate super-resolution model simulations useful for planning, interpreting, and optimizing top-down retrievals, and we discuss favourable conditions (e.g. meteorological) for reliable mass-balance emission rate estimations.

Evaluation of the prediction performance of air quality numerical forecast models in Shenzhen

As an economically intensive city within the greater bay area (GBA), Shenzhen has suffered from severe ozone pollution in recent years. Numerical modeling is an important tool in daily air quality prediction. However, a combination of factors, such as outdated emission inventories and the uncertainty of weather and numeric models, pose challenges for accurately forecasting pollution periods and levels. Therefore, systematic evaluation of the numerical model performance is crucial for better manual revised prediction of the daily MAD8h and air quality index (AQI). In this paper, a multimodel air quality forecast system, which was built in our public-owned monitoring center station, was evaluated to understand the possibilities of improvements. Based on the 2021 observed data of the national air monitoring station, we utilized a series of metrics to access the predicted air quality index (AQI) and pollution concentration levels from models (including WRF-CMAQ, NAQPMS, and WRF-CHEM) and compared them to the manual prediction. The results indicated that WRF-CMAQ performs outstandingly in comprehensive analysis, with a yearly 24 h (hour) forecast accuracy (A) exceeding 91%. The NAQPMS 24 h forecast presented the lowest accuracy (A = 71%) with a high overprediction rate. The forecast accuracy of WRF-CHEM and NAQPMS in the winter period was 100%. However, frequently changing weather patterns interfered with spring forecasting. Forecasters can accurately predict mild pollution cases (A = 81.8% for 24 h, A = 72.7% for 48 h), whereas numerical models (NAQPMS and WRF-CHEM) showed better sensitivity to moderate pollution cases. For fine particulate evaluation, CMAQ's low biases occurred in winter, and the manually revised air quality forecast (MRAQR) normally gave higher prediction values except in pollution cases. Model underestimation could be explained by missing the long-range dust transport contribution from the northern part of China. The ozone 24 h forecast part revealed that WRF-CMAQ exhibited the highest correlation coefficient (R = 0.70, 19.74% < RMSE < 42.7%), whereas NAQPMS showed relatively poor results with the highest ME (43 μg/m3) and MFE (41.92%). Close examination of synoptic information revealed that ozone pollution cases were subjected to the western Pacific subtropical high (WPSH) system, tropical cycle, and regional strong pollution transport. The NAQPMS ozone overprediction could be explained by the overestimation of troposphere transmission from the surroundings during nonconductive weather patterns. The study investigates a theoretical method for model optimization, which provides solid support for precise emission reduction and targeted pollution control.

Health benefits of reducing aircraft pollution: evidence from changes in flight paths

This paper investigates externalities generated by air transportation pollution on health. As a source of exogenous variation, we use an unannounced 5-month trial that reallocated early morning aircraft landings at London Heathrow Airport. Our measure of health is prescribed medications spending on conditions known to be aggravated by pollution, especially sleep disturbances. We observe a significant and substantial decrease in prescribed drugs for respiratory and central nervous system disorders in the areas subjected to reduced air travel between 4:30 am and 6.00 am compared with the control regions. Our findings suggest a causal influence of aviation on health conditions.

Rethinking terrestrial dissolved organic matter in dam reservoirs before mixing: Linking photodegradation and biodegradation and the phenanthrene binding behavior

With the increased construction of dam reservoirs and the demand for water security, terrestrial dissolved organic matter (DOM) has received attention because of its role in regulating water quality, ecological functions, and the fate and transport of pollutants in dam reservoirs. This study investigated the transformations of soil DOM and vegetation DOM of dam reservoirs following photodegradation and biodegradation before conservative mixing, as well as the resultant effects on phenanthrene binding. Based on the results, terrestrial DOM could undergo transformation via photodegradation and biodegradation before conservative mixing in dam reservoirs. Although both processes resulted in substantial decreases in DOM concentrations, the changes in chromophoric DOM and fluorescent DOM depended on the original DOM sources. Furthermore, the photodegradation of terrestrial DOM resulted in more pronounced photobleaching than photomineralization. In addition, photodegradation of terrestrial DOM resulted in the generation of DOM-derived by-products with low molecular weight and low aromaticity, whereas the biodegradation of terrestrial DOM resulted in DOM-derived by-products with low molecular weight and high aromaticity. Subsequently, the photodegradation and biodegradation of terrestrial DOM substantially enhanced the binding affinity of phenanthrene. Soil DOM is prior to vegetation DOM when predicting the ecological risk of HOCs. These results indicate that the terrestrial DOM in dam reservoirs should be reconsidered before conservative mixing. Further studies on the coupling effects of both biogeochemical processes, as well as on the relative contributions of soil DOM and vegetation DOM after transformation to the aquatic DOM in dam reservoirs, are required. This study provides information on the environmental effects of dam construction from the perspective of biogeochemical processes.

Spatial clustering and spillover pathways analysis of O3, NO2, and CO in eastern China during 2017–2021

The eastern China presented the most serious O3 pollution and increasingly prominent regional characteristics. To understand the transport characteristics of O3 and its precursors and identify their potential relationships are of great guiding significance for interregional joint prevention and control. In this study, the annual and seasonal transport networks of O3 and its precursors (NO2 and CO) during 2017–2021 were constructed by applying the complex network method to air quality observations. And the key spatial clusters, the spillover paths and the potential links among pollutants were comprehensively analyzed based on the topological characteristic analysis of the established air pollutant transport networks. As the results showed, O3 pollution in the eastern China was affected by active regional transports of O3 and its precursors. Regional transports of O3, NO2, and CO were more prominent in autumn and showed high synchronization. The regional transport of precursors, especially NOx, was an important cause of regional O3 pollution. Air pollutant transport characteristics varied with seasons and regions, which demonstrating the importance of regulating seasonal and regional differentiated joint prevention and control strategies, especially for NOx. The results of this study can provide science-based guidance for the regional cooperative control of O3 pollution in the eastern China, and the application of complex networks can also provide a new methodological perspective for the study of air pollution transmission.

Modelling of Pollutant Transport in Yamuna River from the Najafgarh Drain, NCT Delhi Using Matlab Software

When the river Yamuna leaves the National Capital Territory of Delhi, its situation further deteriorates. Despite accounting for only 1% of the river’s overall catchment area, this region is responsible for more than half of the pollutants discovered in the Yamuna. The river Yamuna, on the other hand, is Delhi’s only natural resource for maintaining all forms of life. The Yamuna River is currently experiencing a significant level of pollution problem, and in order to control pollution in the Yamuna River, continual analysis is essential. The Yamuna River is contaminated by the discharge of untreated municipal sewage and industrial effluent through seven major drains: Najafgarh, Yamunapur, Sen Nursing Home, Barathpula, Maharani Bagh, Kalkaji, and Tuglakabad. In terms of people and chemicals, continuous sampling takes time and money. The primary objective of this study is to analyse the wastewater samples collected by sub-drains and STP’s to predict the pollutant transportation in river Yamuna from Najafgarh Drain. The study focusses on the only pollutant, i.e., Biochemical Oxygen Demand from the starting point to after the confluence of Najafgarh Drain into river Yamuna. The prediction is to be done by using MATLAB software. This study would help to identify the main sources of sub-drains which are polluting Najafgarh Drain and eventually the river Yamuna. This shows how MATLAB may be used to calculate the pollution load caused by organic waste in the Yamuna River as it flows through Delhi, India’s National Capital Territory. The model numerically solves a series of differential equations to simulate the dissolved oxygen and biochemical oxygen demand parameters in two dimensions. MATLAB is an interactive programming language that may be used to develop algorithms, graphics, and user interfaces in other computer languages. MATLAB helps estimate future water quality using present data, which saves time, labour, and other costs associated with the continuous study. There are various software programmes available in the market for predicting river water quality, however, MATLAB GUI provides an accessible and convenient user interface (Graphical User Interface).

Ineffective implementation of emergency reduction measures against high concentrations of particulate matter in Seoul, Republic of Korea

Since December 30, 2017, the Seoul Metropolitan Government, Republic of Korea, has been implementing emergency reduction measures (ERMs) restricting the operation of industrial sites, thermal power plants, and vehicles when air quality is expected to deteriorate. ERMs are implemented when the present observed concentration of particulate matter (PM) of aerodynamic diameter less than 2.5 μm (PM2.5) and/or the predicted values for the following day exceed a threshold value. In this study, the effectiveness of ERMs was evaluated for 33 days with and 6 days without ERM implementation but where the PM2.5 concentration exceeded the threshold value, until March 15, 2021. Of the 33 days of ERM implementation, on 7 days it was executed despite the thresholds not being met. The ERM on these days might have been properly executed because the pre-notice and implementation of ERM might have reduced the local emissions of air pollutants. Our major findings are that even on days of ERM implementation, there were marginal reductions in vehicle traffic, thermal power generation, and industrial emissions. Second, the concentrations of PM2.5 and related air pollutants in Seoul were almost unchanged for most ERM implementation episodes. Third, most of the 39 (= 33 + 6) days when the air quality worsened were caused by the transboundary transport of air pollutants from China. In conclusion, it was revealed that the currently executed ERM law is insufficient for effectively reducing PM2.5. To achieve the required reductions, it is necessary to undertake stricter policies in Seoul and its neighboring regions.

Research on the Transport of Typical Pollutants in the Yellow Sea with Flow and Wind Fields

In this study, we developed a transport model for typical pollutants in the Yellow Sea using the Lagrangian particle tracking method to analyze the trajectories of fish feed, a common pollutant in the Yellow Sea. The model incorporates the influence of ocean currents and surface winds on pollutant transport and utilizes a series of numerical experiments to simulate pollutant transport. Through statistical analysis of the numerical experiment results, we identified characteristic circles that represent the pollutant distribution patterns. Furthermore, based on the current and wind information within these characteristic circles, we derived an empirical formula to describe pollutant distribution. This formula enables us to predict the spatial distribution of pollutants using available current and wind data. Using this empirical formula, we designed an effective path to avoid pollutant contamination. This approach not only optimizes the utilization of computational resources within the study area but also contributes to the rational planning of navigation routes for aquaculture vessels. Overall, our study provides valuable insights into the transport behavior of fish feed pollutants in the Yellow Sea. The establishment of the empirical formula and the design of effective routes to avoid pollution contribute to the efficient management of pollution and facilitate the planning of marine activities in the region.

Comprehensively exploring the characteristics and meteorological causes of ozone pollution events in Beijing during 2013–2020

Ozone (O3) pollution deteriorated in recent years in Beijing; however, the evolution characteristics and formation mechanism of O3 pollution events (OPEs) lack comprehensive exploration from a long-term perspective. Based on 35-site (Beijing) and multi-city (North China) O3 and meteorological monitoring and reanalysis data, totally 61 OPEs during 2013–2020 were counted in Beijing to reveal their characteristics, the relationship with regional pollution, and meteorological causes. Mild, moderate, and heavy pollution in all OPEs (203 ± 28 μg/m3 for averaged MDA8 O3) accounted for 68.4%, 27.8%, and 3.8% of 291 days, respectively. 78.7% of OPEs were concentrated in May–July. The averaged MDA8 O3 concentration, total days and durations of OPEs increased notably from 2013 to 2020, with a rate of 1.6 μg/m3/yr, 2.7 d/yr, and 0.2 d/yr, respectively. Overall, 90% (53%) of OPEs in Beijing co-occurred with regional pollution covering Beijing-Tianjin-Hebei (North China) under the predominant southerly airflow. Meteorological causes of different levels and spatial distribution of OPEs were explored through multi-scale weather processes. The increasing proportion of southwesterly-westerly synoptic circulation (49%–80%) and mountain-valley breeze (51%–70%), along with enhanced temperature, UV radiation, southerly wind, and temperature inversion and decreased relative humidity, collectively contributed to elevated levels of OPEs. The aforementioned meteorological condition facilitated O3 photochemical reactions, the transport of pollutants, and hindered diffusion. Three spatial types (urban, northern and southern suburban pollution) of OPEs were determined by the intensity and direction of southerly wind. Additionally, daytime O3 pollution elevated the mean peak O3 of nocturnal O3 enhancement events (NOEs) by 31 μg/m3 (41%) mainly induced by convective storms and low-level jets. Our comprehensive investigations of OPEs provide important scientific basis for the precise prediction and control of O3 pollution in Beijing.

Design of a Green Supply Chain Based on the Kano Model Considering Pricing

Nowadays, the design of supply chain networks should be based on environmental issues as well as the needs of customers since the main driver of a supply chain network is customers. Continuous innovation of products requires understanding the features that are most important to customers, and product pricing should be carried out in a way that includes the satisfaction of both customers and manufacturers. This study uses the Kano model to classify product features into different categories. The design of the green supply chain network based on the Kano model has not been investigated in the literature so far. This study examines a green supply chain network including multiple manufacturers, product types, distributors, and carriers that is designed based on Kano’s conceptual model of multiple needs. In the proposed mathematical model of this paper, customer demand is a function of the selling price of the product, transportation pollution is minimized, and a solution based on the Cooperative Game Theory approach is used to solve the mathematical model using the GAMS software. One of the advantages of the proposed mathematical model in this research compared to other supply chain models is that the design needs of the supply chain network based on the Kano model (“must-be”, “one-dimensional”, “attractive” and “indifferent”) can be determined based on customer satisfaction. In addition, the price of the product can be determined according to the satisfaction of both customers and the manufacturers.

A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter

Abstract. Statistical methods, particularly machine learning models, have gained significant popularity in air quality predictions. These prediction models are commonly trained using the historical measurement datasets independently collected at the environmental monitoring stations and their operational forecasts in advance using inputs of the real-time ambient pollutant observations. Therefore, these high-quality machine learning models only provide site-available predictions and cannot solely be used as the operational forecast. In contrast, deterministic chemical transport models (CTMs), which simulate the full life cycles of air pollutants, provide predictions that are continuous in the 3D field. Despite their benefits, CTM predictions are typically biased, particularly on a fine scale, owing to the complex error sources due to the emission, transport, and removal of pollutants. In this study, we proposed a fusion of site-available machine learning prediction, which is from our regional feature selection-based machine learning model (RFSML v1.0), and a CTM prediction. Compared to the normal pure machine learning model, the fusion system provides a gridded prediction with relatively high accuracy. The prediction fusion was conducted using the Bayesian-theory-based ensemble Kalman filter (EnKF). Background error covariance was an essential part in the assimilation process. Ensemble CTM predictions driven by the perturbed emission inventories were initially used for representing their spatial covariance statistics, which could resolve the main part of the CTM error. In addition, a covariance inflation algorithm was designed to amplify the ensemble perturbations to account for other model errors next to the uncertainty in emission inputs. Model evaluation tests were conducted based on independent measurements. Our EnKF-based prediction fusion presented superior performance compared to the pure CTM. Moreover, covariance inflation further enhanced the fused prediction, particularly in cases of severe underestimation.

Transport of the Tumen River water to the Far Eastern Marine Reserve (Posyet Bay) based on in situ, satellite data and Lagrangian modeling using ROMS current velocity output

We study physical mechanisms of the Tumen River water transport in the area of the Posyet Bay (Peter the Great Bay, Sea of Japan). This study is based on the satellite and in situ measurements, and numerical simulation of advection of river water by the current velocity simulated by Regional Ocean Model System (ROMS). The importance of this study is in identification of the reasons of the transport of pollutants into the area of the Far Eastern Marine Reserve. The results of the study showed that such reasons are wind currents and mesoscale cyclonic eddies. These eddies were originally detected on satellite imagery and CTD and bio-optical measurements. The anomalies in the form of spots of the chlorophyll a (CHL) increased concentration were detected on satellite images in fall 2009. The oceanographic sections of CTD and bio-optical measurements through the anomalies show that they are cyclonic eddies. These eddies consist of two cores — upper and lower. The upper core is filled with river waters with low salinity, high values of CHL and colored dissolved organic matter content (CDOM). The lower core is filled with cold saline waters. The ROMS results show that eddies are generated as a result of symmetrical and centrifugal instabilities.

Road dust resuspension in a coastal Atlantic intermunicipal urban area with industrial facilities: Emission factors, chemical composition and ecotoxicity

Road dust resuspension in urban environments can be both a means of transport of pollutants across the various environmental compartments and a source of pollutants itself, becoming a potential threat to human health. With the aim of obtaining emission factors and achieving a detailed chemical characterisation of road dust (RD) in typical Portuguese cities, a sampling campaign was performed in the region of Aveiro. Locations were chosen for intercomparison in various urban environments with different land uses, from the busier city centre and university campus to residential neighbourhoods and harbour-commercial areas with industrial activities. PM10 samples were analysed for organic and elemental carbon (OC and EC) by a thermal-optical technique, elemental composition by PIXE, organic speciation by GC–MS, and ecotoxicology by a luminescence inhibition bioassay with Aliivibrio fischeri. A health risk assessment for elements and PAHs was carried out. Dust loadings of 1.9 ± 1.8 mg PM10 m−2 were registered overall, whereas in the most trafficked areas of city centre they reached more than three times the average. OC accounted for 6.5–15.5% of total PM10, but element oxides represented the largest mass fraction (61.4 ± 8.6%). A strong enrichment was detected mostly for typical traffic-related elements such as Cu, Zn, As, Br, Cr, Ni and Mo and interestingly, Rb and Se. The analysed organic compounds accounted for 3.66–11.0 mg g−1 PM10, including PAHs and aliphatics, with a clear dominance of plasticisers. Some other compounds attributed to non-vehicle sources, such as fatty acid alkyl esters, were also detected. As concerns the 16 priority PAHs, their total mass concentration ranged from 5.58 to 36.3 μg g−1 PM10, with clear variability between sampling spots. All samples caused an ecotoxicological reaction in the bioassay, but samples from harbour and commercial areas proved to be most toxic.

Extreme hydrological regimes of a small urban river: impact on trace element partitioning, enrichment and fluxes.

The input of trace elements from a small urban river (Las River, Toulon, France) located on the northern Mediterranean coast was studied during both base flow and flood events. A 2-year monitoring period of water flow and suspended particulate matter (SPM) showed a typical Mediterranean hydrological regime: a strong increase in water flow and SPM during short flood periods. During the flood event, an up to 2-fold increase in dissolved trace element (DTM) concentrations and particulate trace element content in SPM (PTM) was observed compared to the baseline discharge. The enrichment factor of elements in the SPM ranges from low or moderate for Co, Ni and Cr (1.0-4.7) to extremely high for Cd (157). However, the enrichment factors decrease from base flow to flood, indicating a dilution effect with a large yield of weathering particles with higher particle size. The most significant total trace element loading occurred during flood, ranging from 78% for As and Ni to 91% for Pb, while PTM loading during flood ranged from 35% for As to 77% for Pb. The specific dissolved fluxes during the flood are significantly higher for Pb, Cu and Zn than in the surrounding rivers, indicating specificity in the catchment (lithology). This study shows the importance of monitoring the transport of pollutants through small urban rivers and their potential impact on the coastal region, especially when they enter small and closed bays, as a receiving pool.

An integrated monitoring system (IMS) for air quality: Observations of a unique ozone-exceedance event in Maryland

Ozone (O3) exceedance events in the mid-Atlantic states of the U.S. are typically observed during the summer months. They frequently result from local diurnal emissions of NO2 and VOCs where photochemical production of O3 is most prevalent. Occasionally, summertime O3-exceedances in the region are driven by long-range transport of pollutants or regional nocturnal dynamics. Discussed herein is the use of multiple observation platforms as an integrated monitoring system (IMS) to characterize the spatiotemporal confluence of long-range transport and nocturnal low-level jet induced O3-exceedances impacting air quality in the mid-Atlantic region. The IMS discussed is comprised of enhanced monitoring of vertically resolved observations of O3, atmospheric backscatter, winds, and state variables (e.g., temperature and relative humidity). This is in combination with surface-O3 observations, satellite-retrieved aerosol optical depth (by the moderate resolution imaging spectroradiometer (MODIS)), and simulations of air mass transport by NOAA's hybrid single-particle Lagrangian trajectory (HYSPLIT) model. Here we discuss an exceedance event that impacted the Mid-Atlantic region on May 20, 2021, where seven air monitoring sites in Maryland were driven by the combination of nocturnal low-level jet downmixing of pollutants and long-range transport of biomass-burning pollutants/O3-precursors. The most notable features of this case are this event's deviation from decadal O3-exceedance seasonality trends, the large spatial context of high surface-O3 impacting traditionally non-exceedance sites (sites that have not exceeded in years), the arrival of a well-mixed polluted air mass into the region, and nocturnal increases in surface-O3 induced by NLLJ.

Railway stations as public space: how to promote rail journeys via multi-functional railway stations

ABSTRACT In many European cities, railway stations have become urban hubs in which a variety of functions and uses are focused. These include retail, cafés, offices and housing. They are often also complemented by adjacent amenity open space, in both hard and soft landscaping, alongside a broader provision for other modes, such as public transport, walking and cycling. In this sense, large-scale transport hubs resemble small-scale city centres and, like other urban centres, the public space in stations should meet the needs of a wide range of users. The design and management of railway stations is highly complex and the risk of such nodes failing as quality public spaces is significant. In addition, railway stations play a pivotal role in encouraging public transport use and they have the potential to contribute to a modal shift from more polluting transport modes. We argue that the design and management of such spaces is a key variable in the modal choices many travellers make. Based on empirical research across Europe, this paper presents a set of indicators for assessing the quality of railway stations and their adjacent areas and summarizes our research findings to increase the attractiveness of rail journeys through enhanced public spaces.

Microplastics as an emerging vector of Cr(VI) in water: Correlation of aging properties and adsorption behavior

Microplastics (MPs) are emerging contaminants with growing concerns due to their potential adverse effects on the environment. However, understanding the aging properties and adsorption behavior of MPs is still limited. In this study, we investigated the correlation between the adsorption capacity, aging stages, and aging properties of polyethylene MPs using a correlation equation. Our results revealed that the trends of O/C ratio and contact angle of polyethylene MPs with aging time were fitted to be linear under xenon lamp accelerated aging conditions. Conversely, the trends of other properties such as particle size, crystallinity, and molecular weight with time were fitted to conform to the Boltzmann equation. Moreover, the aging curve data for carbonyl index and molecular weight (Mw) perfectly matched, confirming Mw play a crucial role in verifying the aging process. Additionally, the adsorption amount of polyethylene MPs increased sharply with the increase of aging ages, reaching up to 1.850 mg/g. The adsorption data fit well to the pseudo-second-order kinetics and Langmuir model, suggesting that the adsorption process is dominated by chemisorption. The low pH and low salt concentration is beneficial to the adsorption capacity of MPs onto Cr(VI). Further, a relationship equation was established to predict adsorption risk at different aging stages. These findings provide new insights into the impact of aging on pollutants transport and the fate of MPs, enabling the prediction of adsorption risk of MPs at different aging stages in water environments.

Horizontal flux of ozone in the planetary boundary layer in Hong Kong using wind LiDAR measurements

While the crucial roles of ozone (O3) transport in the planetary boundary layer (PBL) have been acknowledged for some time, there is currently limited knowledge about this aspect primarily due to the limited availability of measurements to determine the characteristics of the PBL. In this study, measurements from a wind Light Detection and Ranging (LiDAR) system were taken to monitor vertical profile of wind pattern at an urban site in Hong Kong in September 2022, a period when the city was frequently impacted by tropical cyclones and experienced severe O3 pollution levels. The PBL height was identified based on the vertical profile of wind speed shear. By combining information on the PBL height, vertical wind profile, and O3 concentration, we performed a cross-sectional analysis to explore the total horizontal flux (THF) of O3 across the PBL in Hong Kong. Throughout the entire study month, the THF of O3 exhibited a predominant easterly component. However, during the O3 pollution episodes, the THF of O3 exhibited a predominant westerly component, indicating an increased regional transport from Greater Bay Area (GBA). The westerly winds between 240° and 300° contributed 61.2% to the total flux of O3 in the PBL during these episodes. In addition, clockwise veering winds were observed from the ground to the top of the PBL, which can be attributed to the Ekman spiral. As a result, during the O3 pollution episodes, the wind with the peak O3 flux shifted from westerly to northwesterly as the height increased in the PBL. The northwesterly THF of O3 between 290° and 300° reached its peak at 600 m above ground level during these episodes. These findings enhance our understanding of the 3D pollutant transports for both long-term averages and short-term pollution episodes in the GBA and Hong Kong.

Ozone and PM2.5 behavior in small cities in southern Brazil

Air pollution is one of the greatest challenges facing humanity today. The number of studies has grown annually, but most of the time they have been conducted in megacities or heavily industrialized regions. In this study, we aimed to evaluate the behavior of O3 and PM2.5 in 5 small cities (&lt; 1500 inhabitants) in southern Brazil, comparing them with reference cities in their micro-regions and with the metropolis Porto Alegre, capital of the state of Rio Grande do Sul. During the short period evaluated, the levels of pollutants in small cities would not differ from those found in the reference cities and were equivalent to the levels in the studied metropolis. Also, during 2 periods (18 to 20 September 2021 and 30 September to 2 October 2021) there were episodes of high levels of PM2.5, superior to the national air quality criteria in 4 of the 5 small cities. The likely origin of the pollutants is the long-distance transport of pollutants from biomass burning in the Amazon. Multiple regression analysis showed little or no influence of local meteorological parameters for O3 and PM2.5 levels, but showed a strong association with pollutant levels in the respective reference cities. Understanding the dynamics of air pollutants in small cities is essential to understand some health outcomes in these populations and has been recently recommended by the World Health Organization.

Identifying the impacts of warming anomalies in the Arctic region and the Tibetan Plateau on PM2.5 pollution and regional transport over China

Arctic region (AR) and Tibetan plateau (TP) are the most sensitive regions to climate change and have synchronously experienced accelerated warming over recent decades. Based on the multi-year observational data of PM2.5 and meteorology, we investigated the modulation of AR and TP's anomalous warming on the variations of PM2.5 pollution and regional transport over central and eastern China (CEC), including major PM2.5 pollution regions in northern China (NC), the Yangtze river delta (YRD), central China (CC), and southern China (SC). Results show that the thermal effects of TP and AR modulated PM2.5 pollution in different ways respectively with prominently influencing the interannual changes of PM2.5 concentrations and heavy PM2.5 pollution occurrences. The impacts of anomalous warming in TP and AR on PM2.5 pollution consistently enhanced regional PM2.5 transport from NC to YRD and SC, while the warming anomalies over AR and TP respectively enhanced and inhibited the southward transport of PM2.5 from NC. In association with the synergistic impact of warming anomalies in AR and TP, the regional PM2.5 transport over CEC presented the inverse patterns of the northward anomalies between NC and CC and the southward anomalies from the eastern part of NC, YRD to SC, forming the regional distribution with negative PM2.5 anomalies in NC and CC and positive PM2.5 anomalies in YRD and SC. Our results highlight the effect of warming anomalies in AR and TP on the PM2.5 pollution over China with the implication of source–receptor relationship of regional transport of air pollutants.