Atmospheric Pollutant Dispersion over Complex Terrain: Challenges and Needs for Improving Air Quality Measurements and Modeling

An analysis of the PM10 chemical composition and its spatial and seasonal variation in Piedmont (Italy) using Raman spectroscopy

Particulate Matter (PM) dramatically affects the well-being of a growing global population, particularly in urban areas. While air quality control is an important and pressing issue, particulate matter analysis typically focuses on size distribution and concentration, offering limited insights into chemical composition and pollutant sources. This study analyzes PM10 samples collected from five air quality monitoring stations across the Piedmont region. Specifically, the two of the stations are located in the urban environment of Turin, a city known as one of Europe's most polluted cities. The analysis has been carried out using primarily Raman Spectroscopy (RS) to identify the main PM components, investigate the different PM compositions, and evaluate the chemical and seasonal variations. Scanning Electron Microscopy (SEM) equipped with an Energy Dispersion X-ray spectrophotometer (EDX) has also been used to obtain further information about the elemental composition and the size distribution. Amorphous carbon, nitrate salt, sulfate salt, iron oxides, and quartz are the main compounds found. The results of our study highlight significant differences in the chemical composition of PM10, indicating variations in the sources and characteristics of PM. Notably, higher levels of nitrate and sulfate particles are linked respectively to cold and warm seasons. Whereas, amorphous carbon and iron oxides are associated with distinct geographic features at the sampling sites, such as traffic conditions. These findings emphasize the importance of understanding the different sources and characteristics of PM10 to develop effective air pollution mitigation strategies in the Piedmont region.

Short-term association of particulate matter and cardiovascular disease mortality in Shanghai, China between 2003 and 2020

Objective

Evidence regarding the effects of particulate matter (PM) pollutants on cardiovascular disease (CVD) mortality remains limited in Shanghai, China. Our objective was to thoroughly evaluate associations between PM pollutants and CVD mortality.

Methods

Daily data on CVD mortality, PM (PM10 and PM2.5) pollutants, and meteorological variables in Shanghai, China were gathered from 2003 to 2020. We utilized a time-series design with the generalized additive model to assess associations between PM pollutants and CVD mortality. Additionally, we conducted stratified analyses based on sex, age, education, and seasons using the same model.

Results

We found that PM pollutants had a significant association with CVD mortality during the study period. Specifically, there was a 0.29% (95%CI: 0.14, 0.44) increase in CVD mortality for every 10 μg/m3 rise in a 2-day average (lag01) concentration of PM10. A 0.28% (95% CI: 0.07, 0.49) increase in CVD mortality was associated with every 10 μg/m3 rise in PM2.5 concentration at lag01. Overall, the estimated effects of PM10 and PM2.5 were larger in the warm period compared with the cold period. Furthermore, males and the older adult exhibited greater susceptibility to PM10 and PM2.5 exposure, and individuals with lower education levels experienced more significant effects from PM10 and PM2.5 than those with higher education levels.

Conclusion

Our findings suggested that PM pollutants have a substantial impact on increasing CVD mortality in Shanghai, China. Moreover, the impacts of air pollution on health may be altered by factors such as season, sex, age, and educational levels.

Assessment the impact of different fuels used in cement industry on pollutant emissions and ambient air quality: a case study in Egypt

This study aims to assess the impact of using different fuels in Egyptian Titan Alexandria Portland Cement Company on emissions and concentrations of pollutants (Total suspended particles (TSP), nitrogen dioxide (NO₂‎), and sulfur dioxide (SO₂)) and their influence on ambient air quality during the period 2014-2020 using AERMOD dispersion model. The results showed that changing the fuel from natural gas in 2014 to coal mixed with alternative fuels (Tire-Derived Fuel (TDF), Dried Sewage Sludge (DSS), and Refuse Derived Fuels (RDF)) in 2015-2020 caused fluctuating variations in pollutant emissions and concentrations. The highest and lowest maximum concentrations of TSP occurred in 2017 and 2014 respectively, where the TSP is positively correlated with coal, RDF, and DSS and negatively correlated with natural gas, diesel, and TDF. Also, the lowest and highest maximum NO₂ concentrations were detected in 2020 and 2016 followed by 2017 respectively, where NO₂ is positively correlated with DSS and negatively correlated with TDF and varies with diesel, coal, and RDF. Moreover, the maximum concentrations of SO₂ were the lowest in 2018 and highest in 2016 followed by 2017 because of its considerable positive correlation with natural gas and DSS and negative correlation with RDF, TDF, and coal. Generally, it was found that increasing the percentage of TDF and RDF with decreasing the percentage of DSS, diesel, and coal will reduce pollutant emissions and concentrations and enhance ambient air quality.

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.

Review of methods for assessing deposition of reactive nitrogen pollutants across complex terrain with focus on the UK

This review is a summary of the most up-to-date knowledge regarding assessment of atmospheric deposition of reactive nitrogen (N r) pollutants across complex terrain in the UK. Progress in the understanding of the mechanisms and quantification of N r deposition in areas of complex topography is slow, as no concerted attempts to measure the components of N r in complex terrain have been made in the last decade. This is likely due to the inherent complexity of the atmospheric processes and chemical interactions which contribute to deposition in these areas. More than 300 studies have been reviewed, and we have consulted with a panel of international experts which we assembled for that purpose. We report here on key findings and knowledge gaps identified regarding measurement and modelling techniques used to quantify deposition of N r across complex terrain in the UK, which depending on definition, may represent up to 60% of land coverage across Great Britain. The large body of peer reviewed papers, reports and other items reviewed in this study has highlighted both the strengths and weaknesses in the tools available to scientists, regulators and policy makers. This review highlights that there is no coherent global research effort to constrain the uncertainties in N r deposition over complex terrain, despite the clearly identified risk of N deposition to ecosystems and water quality. All evidence identified that enhanced N r deposition across complex terrain occurs, and magnitude of the enhancement is not known; however, there are major uncertainties particularly in the differences between modelled and measured wet deposition in complex terrain and representing accurate surface interactions in models. Using simplified estimates for N r deposition, based on current understanding of current measurement and model approaches, an enhancement across UK complex terrain in the range of a factor of 1.4-2.5 (i.e. 40-150% larger than current estimates) is likely over complex upland terrain. If at the upper limits of this, then significantly more ecosystems in the UK would be at a direct risk of degradation, and the potential for long-term non-remediable water quality issues increased.

Location Optimisation in the Process of Designing Infrastructure of Point Pollutant Emitters to Meet Specific Environmental Protection Standards

This article addresses the challenge of searching for the optimal location for a newly designed pollutant emitter (new factory or other facility) in relation to the requirements imposed by environmental protection regulations on the concentrations of selected pollutants in a given area, taking into account the currently existing levels of analysed substances. The paper presents the key issues of the dispersion of pollutants in atmospheric air and pollutant dispersion models. The Gaussian model of a plume, based on the Pasquill diffusion equation, is chosen to simulate the dispersion of pollutants in atmospheric air. The key issue within the paper constitutes the research section responsible for using the Monte Carlo global optimisation method in order to find the optimal location. The proposed algorithm is intended to offer measurable and subjective arguments and options to preliminary discussions on choosing a location for new factories, while such discussions choices should be fact-based and ecologically acceptable instead of fulfilling only political or economical goals. The paper is intended to present the need for easily interpretable arguments for discussions and responsible decisions on choosing the lowest-impact location of pollutant emitters to the scientific community.

Data Filling of Micrometeorological Variables in Complex Terrain for High-Resolution Nowcasting

In this paper, two different computationally inexpensive methods for nowcasting/data filling spatially varying meteorological variables (wind velocity components, specific humidity, and virtual potential temperature) covering scales ranging from 100 m to 5 km in regions marked by complex terrain are compared. Multivariable linear regression and artificial neural networks are used to predict micrometeorological variables at eight locations using the measurements from three nearby weather stations. The models are trained using data gathered from a system of eleven low-cost automated weather stations that were deployed in the Cadarache Valley of southeastern France from December 2016 to June 2017. The models are tested on two held-out periods of measurements of thermally-driven flow and synoptically forced flow. It is found that the models have statistically significant performance differences for the wind components during the synoptically driven flow period (p = 6.6 × 10−3 and p = 2.0 × 10−2 for U and V, respectively), but perform the same otherwise. These methods can be used to spatially fill gaps in micrometeorological datasets. Recommended future work should include statistically interpreting the predictive models and testing their capabilities on meteorological datasets from different locations.

Sensitivity of Pollutant Concentrations to the Turbulence Schemes of a Dispersion Modelling Chain over Complex Orography

Atmospheric circulation over mountainous regions is more complex than over flat terrain due to the interaction of flows on various scales: synoptic-scale flows, thermally-driven mesoscale winds and turbulent fluxes. In order to faithfully reconstruct the circulation affecting the dispersion and deposition of pollutants in mountainous areas, meteorological models should have a sub-kilometer grid spacing, where turbulent motions are partially resolved and the parametrizations of the sub-grid scale fluxes need to be evaluated. In this study, a modelling chain based on the Weather Research and Forecasting (WRF) model and the chemical transport model Flexible Air Quality Regional Model (FARM) is applied to estimate the pollutant concentrations at a 0.5 km horizontal resolution over the Aosta Valley, a mountainous region of the northwestern Alps. Two pollution episodes that occurred in this region are reconstructed: one summer episode dominated by thermally-driven winds, and one winter episode dominated by synoptic-scale flows. Three WRF configurations with specific planetary boundary layer and surface layer schemes are tested, and the numerical results are compared with the surface measurements of meteorological variables at twenty-four stations. For each WRF configuration, two different FARM runs are performed, with turbulence-related quantities provided by the SURface-atmosphere interFace PROcessor or directly by WRF. The chemical concentrations resulting from the different FARM runs are compared with the surface measurements of particulate matter of less than 10 µm in diameter and nitrogen dioxide taken at five air quality stations. Furthermore, these results are compared with the outputs of the modelling chain employed routinely by the Aosta Valley Environmental Protection Agency, based on FARM driven by COSMO-I2 (COnsortium for Small-scale MOdelling) at 2.8 km horizontal grid spacing. The pollution events are underestimated by the modelling chain, but the bias between simulated and measured surface concentrations is reduced using the configuration based on WRF turbulence parametrizations, which imply a reduced dispersion.

Air quality biomonitoring through Olea europaea L.: The study case of "Land of pyres"

The "Land of pyres", namely "La Terra dei Fuochi", is an area of Campania region (South-Italy), highly inhabited and comprises between the Provinces of Naples and Caserta, sadly known worldwide for the criminal activities related to the illegal waste disposal and burning. These fires, concomitantly with traffic emissions, might be the source of potential toxic element (PTE) dangerous for the human health and causing pathologies. In the framework of Correlation Health-Environment project, funded by the Campania region, eight municipalities (of area "Land of pyres") and three remote sites have been bio-monitored using the olive (Olea europaea L.) plants as biomonitors. Leaves of olive plants were collected in each assayed municipality and the concentration of 11 metal(loid)s was evaluated by means of ICP-OES. Our findings revealed that the air of these municipalities was limitedly contaminated by PTE; in fact, only Sb, Al and Mn were detected in the olive leaves collected in some of the assayed municipalities and showed a high enrichment factors (EC) manly due, probably, to the vehicular traffic emissions. Furthermore, the concentrations of the other assayed PTEs were lower than those of Sb, Al and Mn. For these reasons we suppose that their emissions in the troposphere have been and are limited, and they mainly have a crustal origin. Even if our data are very comforting for those urban area, regarded by many as one of the most contaminated one in Italy, a great environment care, in any case, is always needed.

Effect of Extreme Temperatures and Driving Conditions on Gaseous Pollutants of a Euro 6d-Temp Gasoline Vehicle

Gaseous emissions of modern Euro 6d vehicles, when tested within real driving emissions (RDE) boundaries, are, in most cases, at low levels. There are concerns, though, about their emission performance when tested at or above the boundaries of ambient and driving conditions requirements of RDE regulations. In this study, a Euro 6d-Temp gasoline direct injection (GDI) vehicle with three-way catalyst and gasoline particulate filter was tested on the road and in a laboratory at temperatures ranging between −30 °C and 50 °C, with cycles simulating urban congested traffic, uphill driving while towing a trailer at 85% of the vehicle’s maximum payload, and dynamic driving. The vehicle respected the Euro 6 emission limits, even though they were not applicable to the specific cycles, which were outside of the RDE environmental and trip boundary conditions. Most of the emissions were produced during cold starts and at low ambient temperatures. Heavy traffic, dynamic driving, and high payload were found to increase emissions depending on the pollutant. Even though this car was one of the lowest emitting cars found in the literature, the proposed future Euro 7 limits will require a further decrease in cold start emissions in order to ensure low emission levels under most ambient and driving conditions, particularly in urban environments. Nevertheless, motorway emissions will also have to be controlled well.

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

Transport and Exchange Processes in the Atmosphere over Mountainous Terrain: Perspectives and Challenges for Observational and Modelling Systems, from Local to Climate Scales

This Editorial offers an overview of the results presented in the series of coordinated articles included in the Atmosphere special issue on Atmospheric Processes over Complex Terrain. In particular, the variety of approaches and methods, as well as the main outcomes of recent progress in the field, are outlined, along with open questions and challenges for future developments. The possible outreach of future research in the field is also pointed out, especially in connection with the ongoing international cooperation initiative Multi-scale transport and exchange processes in the atmosphere over mountains programme and experiment (TEAMx).

Benzo[a]pyrene in the Ambient Air in the Czech Republic: Emission Sources, Current and Long-Term Monitoring Analysis and Human Exposure

This paper provides a detailed, thorough analysis of air pollution by benzo[a]pyrene (BaP) in the Czech Republic. The Czech residential sector is responsible for more than 98.8% of BaP, based on the national emission inventory. According to the data from 48 sites of the National Air Quality Monitoring Network, the range of annual average concentration of BaP ranges from 0.4 ng·m−3 at a rural regional station to 7.7 ng·m−3 at an industrial station. Additionally, short-term campaign measurements in small settlements have recorded high values of daily benzo[a]pyrene concentrations (0.1–13.6 ng·m−3) in winter months linked to local heating of household heating. The transboundary contribution to the annual average concentrations of BaP was estimated by the CAMx model to range from 46% to 70% over most of the country. However, the contribution of Czech sources can exceed 80% in residential heating hot spots. It is likely that the transboundary contribution to BaP concentrations was overestimated by a factor of 1.5 due to limitations of the modeling approach used. During the period of 2012–2018, 35–58% of the urban population in the Czech Republic were exposed to BaP concentrations above target. A significant decreasing trend, estimated by the Mann-Kendall test, was found for annual and winter BaP concentrations between 2008 and 2018.