Removal Of Air Pollutants Research Articles

In situ synthesis of Ti3C2Tx/TiO2 for efficient photocatalytic removal of NOx

Photocatalysts are crucial in facilitating the degradation of air pollutants. Leveraging the unique structural attributes of titanium-containing MXene Ti3C2Tx, this study presents the first synthesis of multilayer and few-layer Ti3C2Tx/TiO2 with Schottky junctions via an in situ hydrothermal method for NOₓ degradation. XRD, SEM, TEM, and XPS analyses confirmed the successful assembly of Ti3C2Tx/TiO2 photocatalysts. In NOₓ removal experiments, Ti3C2Tx/TiO2 with a few-layer structure achieved a NO removal rate of 63.7 % and a NO₂ generation rate of only 8.4 % within 30 min. Conversely, the multilayer Ti3C2Tx/TiO2 exhibited a NO removal rate of 59.4 % and a NO₂ generation rate of 13.7 %. Cyclic performance tests demonstrated that the few-layer Ti3C2Tx/TiO2 possesses superior stability compared to its multilayer counterpart. Electron paramagnetic resonance (EPR) spectroscopy results indirectly confirmed that Schottky junction formation significantly enhanced carrier separation. Based on EPR and NOₓ degradation findings, potential pathways for NOₓ degradation were deduced. This research offers valuable insights into utilizing MXene for air pollutant removal and elucidating the photocatalytic oxidation mechanism.

Transforming urban air quality: Green infrastructure strategies for the urban centers of Ethiopia

Urban green infrastructure (GI) plays a crucial role in improving air quality by removing pollutants and reducing emissions from structures. However, in Ethiopia, inadequate GI planning, largely due to limited awareness among planners and policymakers, can undermine the benefits of GI and worsen urban air quality issues. In this study, we demonstrate how the GI strategy approach can enhance air quality and assess the negative impacts of biogenic volatile organic compounds (BVOCs) emitted by certain tree species in Ethiopia, using Hawassa as a case study. We utilized a customized i-Tree Eco model to estimate annual pollutant removal and BVOC emissions and applied the Kriging method in ArcGIS to map their spatial distribution. In Hawassa, GI systems removed 274.2 t of pollutants annually, valued at $1.79 million, with SO2 being the most and CO the least removed pollutants. Air pollution removal was highest during the dry season (37.4%) compared to the long (29.7%) and short rainy seasons (32.9%). Conversely, trees emitted 35.78 t of BVOCs annually, with monoterpene and isoprene being nearly equal contributors. Eucalyptus genus, Casuarina equisetifolia, and Schinus molle species were the top BVOC emitters despite their low population percentages in the study area. While GI types such as urban parks and institutional compounds are effective at pollutant removal, they also exhibit higher BVOC emissions. Our findings highlight the need for optimized species selection, improved GI planning, and enhanced policy support to maximize GI effectiveness, providing valuable insights for planners and policymakers in integrating GI into urban spatial planning.

Trace benzene capture by decoration of structural defects in metal-organic framework materials.

Capture of trace benzene is an important and challenging task. Metal-organic framework materials are promising sorbents for a variety of gases, but their limited capacity towards benzene at low concentration remains unresolved. Here we report the adsorption of trace benzene by decorating a structural defect in MIL-125-defect with single-atom metal centres to afford MIL-125-X (X = Mn, Fe, Co, Ni, Cu, Zn; MIL-125, Ti8O8(OH)4(BDC)6 where H2BDC is 1,4-benzenedicarboxylic acid). At 298 K, MIL-125-Zn exhibits a benzene uptake of 7.63 mmol g-1 at 1.2 mbar and 5.33 mmol g-1 at 0.12 mbar, and breakthrough experiments confirm the removal of trace benzene (from 5 to <0.5 ppm) from air (up to 111,000 min g-1 of metal-organic framework), even after exposure to moisture. The binding of benzene to the defect and open Zn(II) sites at low pressure has been visualized by diffraction, scattering and spectroscopy. This work highlights the importance of fine-tuning pore chemistry for designing adsorbents for the removal of air pollutants.

Comprehensive Review of Fly Ash: Environmental Impact and Applications

ABSTRACTFly ash (FyA), a byproduct from coal combustion in power plants, has become increasingly valuable due to its pozzolanic properties. Primarily, FyA finds applications in the construction industry, including road and brick construction, forest road building, and the cement industry. When added to concrete, it enhances splitting tensile strength, compressive strength, and workability, while also reducing the environmental impact of cement production. Beyond construction, FyA is utilized for air pollutant removal and serves as an adsorbent for various contaminants. It also plays a role in creating geopolymers and nanocomposites, promoting the development of eco‐friendly construction materials. This review article presents current data on thermal power plants (ThPPs) in India, the challenges in FyA management, and its environmental impact. It also discusses relevant Indian policies and highlights ongoing research aimed at improving the efficiency and expanding the applications of FyA in various industrial sectors, such as battery manufacturing, zeolite synthesis, and cenosphere extraction. These efforts underscore FyA's potential in supporting sustainable practices. The findings of this review address critical issues related to FyA. By reducing the environmental footprint of cement manufacturing, removing air pollutants, and acting as an adsorbent for various contaminants, FyA demonstrates significant potential in pollution mitigation. It also contributes to the development of eco‐friendly construction materials and promotes sustainability in the construction sector. Effective management practices are essential to minimize FyA's negative impact on human health and the environment. The article emphasizes the need for greater awareness and implementation of policies to address these issues comprehensively. By providing a detailed understanding of the benefits and challenges associated with FyA, it aims to pave the way for more effective and sustainable utilization of this industrial byproduct.

Light Precipitation rather than Total Precipitation Determines Aerosol Wet Removal.

Precipitation scavenging is an important sink for both organic and inorganic pollutants in the atmosphere. However, there has been controversy over the relative importance of different precipitation characteristics (i.e., the precipitation amount, intensity, frequency, and duration) in the removal of air pollutants. It is critical to reach a consensus on which precipitation characteristics are most significant for aerosol wet removal. In this study, the analysis of multisource in situ observations of aerosol wet deposition worldwide indicates that the precipitation frequency plays a first-order role in scavenging aerosols. This is because large amounts of air pollutants are efficiently removed at precipitation initiation. As the duration and amount of precipitation increase, the scavenging efficiency decreases sharply. Consequently, it is featured that light precipitation, due to its high frequency of occurrence, rather than total precipitation, determines climatological aerosol wet deposition. To further confirm this, a state-of-the-art global climate model with convection resolved is modified to reduce the light precipitation frequency in both stratiform and convective cloud regimes. Results show widespread increases in aerosol optical depth (AOD) due to the reduced wet deposition. The spatial distribution of aerosol wet deposition changes resembles that of changes in the light precipitation frequency rather than that of total precipitation changes. These findings are consistent with those from the Coupled Model Intercomparison Project Phase 6 multimodel simulations, which show that the intermodel uncertainty in simulated AOD correlates more strongly with the uncertainty in light precipitation frequency than with that in total precipitation.

Assessment of air pollution removal by urban trees based on the i-Tree Eco Model: The case of Tehran, Iran.

Air quality concerns have become increasingly serious in metropolises such as Tehran (Iran) in recent years. This study aims to assess the contribution of urban trees in Tehran toward mitigating air pollution and to evaluate the economic value of this ecosystem service using the i-Tree Eco model. To accomplish this objective, we utilized Tehran's original land use map, identifying five distinct land use categories: commercial and industrial, parks and urban forests, residential areas, roads and transportation, and urban services. Field data necessary for this analysis were collected from 316 designated plots, each with a radius of 11.3 m, and subsequently analyzed using the i-Tree Eco model. The locations of these plots were determined using the stratified sampling method. The results illustrate that Tehran's urban trees removed 1286.4 tons of pollutants in 2020. Specifically, the annual rates of air pollution removal were found to be 134.8 tons for CO; 299.7 tons for NO2; 270.3 tons for O3; 0.7 tons for PM2.5; 489.4 tons for PM10 (particulate matter with a diameter size between 2.5 and 10 µm); and 91.5 tons for SO2, with an associated monetary value of US$1 536 619. However, despite this significant removal capacity, the impact remains relatively small compared with the total amount of pollution emitted in 2020, accounting for only 0.17%. This is attributed to the high emissions rate and low per capita green space in the city. These findings could serve as a foundation for future research and urban planning initiatives aimed at enhancing green spaces in urban areas, thereby promoting sustainable urban development. Integr Environ Assess Manag 2024;00:1-11. © 2024 SETAC.

Air pollutant removal performance using a BiLSTM-based demand-controlled ventilation method after tunnel blasting

Efficient tunnel ventilation is essential for ensuring construction safety and protecting personnel health during tunnel construction. This study proposes a demand-controlled ventilation (DCV) method on the basis of deep learning algorithm to both improve pollutant removal efficiency and reduce energy consumption. The DCV method utilizes a two-layer bidirectional long short-term memory algorithm (BiLSTM) to predict pollutant concentrations. The air volume is dynamically adjusted based on the gaseous pollutant removal requirements. The coefficient of ventilation performance (COVP) is proposed to evaluate the performance of two ventilation methods (DCV and constant air-volume ventilation (CAV)) through computational fluid dynamics (CFD) simulations. The results show that the DCV results in a lower maximum average CO concentration and higher removal efficiency in the heading area (372.3 mg/m3) than the CAV does (404.1 mg/m3). The fan's energy consumption of DCV is 64.6% lower than that of CAV during a 1000 s ventilation period. The COVPs for both methods exhibit temporal variation and achieves their maximums (2.25 for DCV and 0.741 for CAV) after reaching the constraint conditions (air volume threshold). The DCV method expedites pollutant elimination, reduces construction waiting period, and minimizes energy consumption, providing a novel application of a deep learning algorithm in construction engineering.

Quantifying Regulating Ecosystem Services of Urban Trees: A Case Study of a Green Space at Chungnam National University Using i-Tree Eco

Urban green spaces (UGSs) provide numerous ecosystem services (ESs) that are essential to the well-being of the residents. However, these services are often neglected in regional urban development and spatial planning. This study quantified the ESs of a 10.25 ha UGS at Chungnam National University, Daejeon, Republic of Korea, comprising 27 species with 287 tree individuals, using i-Tree Eco. Key regulating ESs investigated included air pollution removal, carbon storage and sequestration, oxygen production, energy use reduction, avoidance of surface runoff, and replacement and functional values. Results revealed significant annual environmental benefits: 131 kg air pollutants removed (USD 3739.01 or ₩5.16 M), 1.76 Mg carbon sequestered, which is equivalent to 0.18 Mg CO2 ha−1 yr−1 (USD 289.85 or ₩0.40 M), 2.42 Mg oxygen produced, energy savings (including carbon offset) valued at USD 391.29 (₩0.54 M), and 203 m3 reduction in surface runoff (USD 413.09 or ₩0.57 M). The annual total benefits of these urban trees amounted to USD 4833.86 (₩6.67 M), USD 16.83/tree, or USD 0.089/capita. Additionally, these trees had replacement and functional values estimated at USD 311,115.17 (₩429.3 M). The study underscores that species selection and abundance of urban trees are fundamental for maximizing the ES delivery in urban areas, highlighting the role of UGSs in ecological and economical sustainability in cities. These insights are valuable for urban planners and policymakers to optimize benefits of UGSs in cities.

Optimizing green infrastructure strategies for microclimate regulation and air quality improvement in urban environments: A case study

With an increasing global urban population andassociated health concerns, understanding the effects of urban microclimate and air quality is crucial. This study aims to assess the influence of different types and locations of greenery, along with building heights and wind orientation, on urban canyon microclimate and air quality. Focusing on PM10, PM2.5, and NOx concentrations in a hot-arid district, the research employs simulation-based analysis. Results indicate that stepped buildings with green walls exhibit the highest temperature (18.02°C), while scenarios featuring two rows of deciduous trees showcase the lowest temperature (17.56°C) but higher pollution levels. Notably, scenarios lacking trees exhibit elevated temperatures. The study introduces a novel ventilation design pattern for effective air pollutant removal and proposes a scenario with extensive green coverage on streets, walls, and rooftops, incorporating appropriate planting techniques and plant selection. The findings offer valuable insights for urban designers and architects seeking to create more sustainable and environmentally friendly cities.

Flame made low Pt loading catalysts supported on different metal oxides for catalytic combustion of CO and CH4

Catalytic combustion is an effective approach to remove air pollutants from various emission sources. For this purpose, supported noble metal catalysts are preferred in commercial applications due to their outstanding catalytic activity for eliminating CO, hydrocarbon compounds and NOx. In this paper, we employ the flame spray pyrolysis method to prepare a series of Pt-based catalysts with four different supports (TiO2, ZrO2, MgO and ZnO) and variable low Pt loadings for catalytic combustion of CO and CH4. The performance of 0.5 Pt/TiO2 is the best in all samples, in which the T90 temperatures are 107 and 500 °C for 90% conversion of CO and CH4, respectively. To examine its thermal stability, a time-on-stream test at 700 °C for 420 min is carried out, resulting in a decrease of about 5% in the final conversion of CH4. The X-ray diffraction results show that TiO2 support is a mixed phase with a major amount of anatase and a small amount of rutile other than a pure phase of ZrO2, MgO and ZnO. Furthermore, X-ray photoelectron spectroscopy analysis and high-angle annular dark-field scanning transmission electron microscopy observation show that when the Pt loading is low, the Pt species exist as highly dispersed single atoms on the surface of the TiO2 support. As the Pt loading gradually increases, the state of the Pt species transitions from single atoms to Pt clusters, resulting in a decrease in dispersion. Ultimately, the Pt can successfully accumulate on the surface of the TiO2 nanoparticles, providing abundant active sites for efficient catalytic combustion reactions.

Synthesis of TiO2/SBA-15 Nanocomposites by Hydrolysis of Organometallic Ti Precursors for Photocatalytic NO Abatement

The development of advanced photocatalysts for air pollution removal is essential to improve indoor air quality. TiO2/mesoporous silica SBA-15 nanocomposites were synthesized using an organometallic decoration method, which leverages the high reactivity of Ti precursors to be hydrolyzed on the surface water groups of silica supports. Both lab-made Ti(III) amidinate and commercial Ti(IV) amino precursors were utilized to react with water-rich SBA-15, obtained through a hydration process. The hydrated SBA-15 and the TiO2/SBA-15 nanocomposites were characterized using TGA, FTIR, 1H and 29Si NMR, TEM, SEM, N2 physisorption, XRD, and WAXS. This one-step TiO2 decoration method achieved a loading of up to 51.5 wt.% of approximately 9 nm anatase particles on the SBA-15 surface. This structuring provided excellent accessibility of TiO2 particles for photocatalytic applications under pollutant gas and UV-A light exposure. The combination with the high specific surface area of SBA-15 resulted in the efficient degradation of 400 ppb of NO pollutant gas. Due to synergistic effects, the best nanocomposite in this study demonstrated a NO abatement performance of 4.0% per used mg of TiO2, which is 40% more efficient than the reference photocatalytic material TiO2 P-25.

A systematic review on phytoremediation of indoor air pollution

Degradation of Indoor Air Quality (IAQ) due to confined spaces and insufficient ventilation has become a serious concern to human health. Published literature has established phytoremediation as an efficient removal mechanism of indoor air pollutants such as formaldehyde, Benzene, Toluene, Ethyl benzene, Xylene (BTEX), Volatile Organic Compounds (VOCs), and Particulate Matter (PM) using potted plants. This review discusses both conventional and enhanced phytoremediation for removing air pollutants and the parameters influencing the removal efficiencies. A literature review was conducted following the PRISMA guidelines to identify published literature on indoor air phytoremediation. After eliminating duplicates and reviewing articles, the articles related to indoor air phytoremediation from 2011 to the present were selected. The database was managed using Mendeley reference manager. Indoor air pollutants can be removed efficiently through phytoremediation using potted plants. Chlorophytum comosum removed the broadest range of contaminants, whereas Epipremnum aureum is the frequently used plant species for pollutant removal. Adding enhancing factors to the plant enhances their ability to remove pollutants. Inoculation of plants with soil bacteria such as Bacillus cereus ERBP is the most common enhancement method reported. The present study highlighted advancements in phytoremediation and factors affecting the pollutant removal efficiencies of plants. The findings demonstrated that enhanced phytoremediation is more effective at removing pollutants than the conventional method. Depending on the plant species used, the removal of indoor air pollutants may vary. The findings suggested that a combination of various plant species could be used to remove indoor air pollutants more efficiently.

The Added Value of Urban Trees (Tilia tomentosa Moench, Fraxinus excelsior L. and Pinus nigra J.F. Arnold) in Terms of Air Pollutant Removal

The serious densification of human settlements necessitates an increase in the role and importance of green infrastructures in the overall functioning of urban ecosystems. Accordingly, the aim of the present study was to (1) assess the efficiency of air pollutant removal (potentially toxic elements) of three common ornamental trees (Tilia tomentosa Moench, Fraxinus excelsior L. and Pinus nigra J.F. Arnold) and (2) model the air quality regulatory services (removal of PM10, PM2.5 and NO2). Three different approaches were applied—enrichment factor (EF) and metal accumulation factor (MAI) per tree species, as well as simulation modeling for the whole urban forest. The MAI values of the three studied species were found to be very similar, in the range of 22.35 to 23.08, which suggests that these species could be a good choice for planting in urban areas with worsened air quality. The highest EF values were observed for U (3–18), followed by As (1.6–2.56) and Sr (0.87–2.46). The potential of urban forests in countering air pollution was highlighted by three simulated scenarios for PM10, PM2.5 and NO2 removal. The highest removal efficiency was calculated for evergreen species, followed by the mixed composition of deciduous (90%) and evergreen trees (10%), and the scenario with wholly deciduous trees had the lowest one. The contribution of nature-based solutions in meeting air quality standards and enhancing resilience in urban areas was clearly demonstrated. The functional complementarity of the different functional tree groups (coniferous, evergreen and deciduous broad-leaved species) was proven to be crucial for the support of both functional stabilities of the phytocenosis under diverse climatic conditions and during the change of seasonal cycles in the vegetation.

Assessment of Pesticide Residues in some Selected Plants in Billliri and Kaltungo Local Government Area, Gombe State, Nigeria

The study aimed to assess pesticide residues in selected plants in the Billiri and Kaltungo local government areas of Gombe State, Nigeria. Parts of the selected plants, namely Acacia nilotica, Piliostigma reticulatum, and Calotropis procera were randomly collected, including leaves, stem bark, and roots. These plant parts were washed with tap water and de-ionized water to remove air pollutants, then oven-dried at 105°C to eliminate moisture. The dried samples were pulverized using an agate pestle and mortar and sieved through a 0.5 mm mesh to obtain a uniform particle size. Pesticide residues were determined using gas chromatography (GC). Fourteen organochlorine pesticide residues were detected, including Delta-Lindane, Alpha-Lindane, Gamma-Lindane, Heptachlor, Aldrin, Heptachlor Epoxide, Endosulfan I, P,P-DDE, Endrin, Endosulfan II, P,P-DDD, P,P-DDT, and Methoxychlor.Based on the results from all locations, the lowest concentrations were below the maximum residue limit as per FAO/WHO guidelines, which range from 0.001 to 0.5 ppm. The highest concentrations of organochlorine pesticide residues reported in this study may be attributed to environmental pollution and pesticide use, consistent with the mean values reported in soils from Numan LGA in Adamawa State, Nigeria. In the intricate tapestry of modern agriculture, the assessment of organochlorine pesticide residues in the distinct agroecological locales of Billiri and Kaltungo Local Government Areas unravels a compelling narrative of historical legacies, environmental intricacies, and imperatives for change. Keywords: Pesticide residues, Organochlorine pesticides, Acacia nilotica, Piliostigma reticulatum, Calotropis procera, Environmental pollution and Gas chromatography (GC)

Evaluating the Particulate Matter and Carbon Dioxide Reduction of Four Broad-leaved Evergreen Plants

Background and objective: Since people spend 70-80% of their time indoors, the quality of indoor air has become a crucial factor in overall health. Therefore, poor indoor air quality can have significant adverse effects on our well-being. Common indoor air pollutants are particulate matter (PM) and carbon dioxide (CO2). Plants can remove PM and CO2 through the photosynthesis process and leaf surfaces, and regulate the temperature and humidity of the air. By analyzing the PM and CO2 reduction of four broad-leaved evergreen plants, this study aims to provide data for air purification in indoor spaces.Methods: The four different plant species (Neolitsea sericea (Blume) Koidz., Coffea arabica L., Photinia glabra(Thunb.) Franch. and Sav., and Farfugium japonicum (L.) Kitam.) were selected for this study. Mosquito coils and a CO2 cylinder were the primary sources of PM and CO2. These pollutants were injected into a closed acrylic chamber with plants, and the air quality within the chamber was monitored for a duration of five hours. The plants' effectiveness in reducing carbon dioxide was evaluated through the clean air delivery rate (CADR), while their ability to reduce PM was assessed by analyzing the PM reduction rate. Photosynthetic rates and leaf area were also measured to determine the correlation between air pollution removal and these factors.Results: The ability to remove PM and CO2 varied among plants. Plants with higher rates of photosynthesis were more effective in reducing PM and CO2 than those with lower rates. Among the four plant species, C. arabica and P. glabra were more effective in removing PM and CO2 than the other species. The chamber containing plants exhibited higher humidity and lower temperatures compared to the chamber without plants.Conclusion: These findings suggest that plants can play a significant role in improving indoor air quality. Not only do they effectively reduce levels of PM and CO2, but they also contribute to the regulation of indoor temperature and humidity. The implications of these results highlight the potential of integrating plants into indoor spaces as a natural and multifaceted solution for creating healthier and more comfortable environments.

Advances in amelioration of air pollution using plants and associated microbes: An outlook on phytoremediation and other plant-based technologies

Globally, air pollution is an unfortunate aftermath of rapid industrialization and urbanization. Although the best strategy is to prevent air pollution, it is not always feasible. This makes it imperative to devise and implement techniques that can clean the air continuously. Plants and microbes have a natural potential to transform or degrade pollutants. Hence, strategies that use this potential of living biomass to remediate air pollution seem to be promising. The simplest future trend can be planting suitable plant-microbe species capable of removing air pollutants like SO2, CO2, CO, NOX and particulate matter (PM) along roadsides and inside the buildings. Established wastewater treatment strategies such as microbial fuel cells (MFC) and constructed wetlands (CW) can be suitably modified to ameliorate air pollution. Green architecture involving green walls and green roofs is facile and aesthetic, providing urban ecosystem services. Certain microbe-based bioreactors such as bioscrubbers and biofilters may be useful in small confined spaces. Several generative models have been developed to assist with planning and managing green spaces in urban locales. The physiological limitations of using living organisms can be circumvent by applying biotechnology and transgenics to improve their potential. This review provides a comprehensive update on not just the plants and associated microbes for the mitigation of air pollution, but also lists the technologies that are available and/or can be modified and used for air pollution control. The article also gives a detailed analysis of this topic in the form of strengths-weaknesses-opportunities-challenges (SWOC). The strategies mentioned in this review would help to attain corporate Environmental Social and Governance (ESG) and Sustainable Development Goals (SDGs), while reducing carbon footprint in the urban scenario. The review aims to emphasise that urbanization is possible while tackling air pollution using facile, green techniques involving plants and associated microbes.

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

AbstractWe present a variable‐resolution global chemistry‐climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban‐to‐rural chemical regimes, mesoscale convective systems, and land‐surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi‐decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25‐km uniform‐resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal‐to‐diurnal cycles and extremes, notably reducing the central US dry‐and‐warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process‐level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land‐biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

Examining regulating ecosystem service provision by brownfield and park typologies and their urban distribution

Environmental hazards including air pollution, heat waves, and flooding are pressing issues in cities. In response, many cities are pledging to increase green infrastructure, adopting nature-based solutions for enhancing resilience through ecosystem service provision. At the same time, urban densification is increasingly considered necessary to limit urban sprawl, where redevelopment of brownfield is often promoted as an alternative to development of greenbelt land. Consequently, while the drive to install additional green infrastructure is intensifying, the synchronous loss of brownfield vegetation may result in unintentional net losses. It is therefore essential to evaluate brownfield’s contribution to ecosystem service provision. Here we present a comparative analysis of the regulating ecosystem services provided by brownfield and park trees in Greater Manchester, UK. Parks were selected as a comparator as they represent the most abundant and widely distributed types of open green space, and typically contain a high proportion of trees. Ecosystem service provision was evaluated across statistically defined typologies of twenty-six brownfield and twelve park types (varying in terms of landscape metrics, land, and canopy cover) using i-Tree Canopy. In terms of carbon storage brownfield (3194 ha) provided an estimated 52,765 t of carbon storage and annual carbon sequestration of 2101 t/y, for parks (4128 ha), 143,064 t of carbon storage, carbon sequestration of 5696 t/y. Annual air pollution removal is estimated at 313 t/y of air pollution removal for brownfields, and 849 t/y for parks. Avoided surface water runoff is estimated at 135,018 m3/y for brownfields and 366,280 m3/y for parks. In densely built areas, brownfields provided approximately five times more regulating ecosystem services than parks, and several types of vegetated brownfield provided more regulating ecosystem services than many types of park. We conclude that brownfield is an important component of green infrastructure, where this knowledge is critical to inform planning and management, prevent loss of ecosystem services, and identify where strategic greening of brownfield may address inequities in existing green infrastructure.

Air pollution removal with urban greenery – Introducing the Vegetation Impact Dynamic Assessment model (VIDA)

Urban greenery is identified as a potential tool in air pollution mitigation. However, the impact is still debated. This paper introduces the innovative VIDA (Vegetation Impact Dynamic Assessment) model, specifically designed to quantify air pollution removal through deposition on vegetation. The VIDA model offers an advanced representation of vegetation that could be integrated into urban air quality dispersion models in the future. Furthermore, the model serves as a valuable tool for exploring the intricate interactions among deposition, resuspension, and wash-off processes, as well as understanding how meteorological conditions and various leaf traits influence these processes.The current version of the model focuses on particulate matter (PM) and encompasses a range of processes, including deposition on vegetation surfaces, encapsulation within the waxy cuticle, wind-driven resuspension, and wash-off. Additionally, the model takes into consideration dynamic changes in PM concentrations on the leaf surface over time, incorporating factors such as PM size fractions, meteorological conditions, and leaf characteristics. This comprehensive approach allows for the evaluation of various species or species groups based on their distinct traits. The VIDA model effectively reproduces measured data, yet continued evaluation remains crucial as new data emerges. Notably, challenges were encountered due to data scarcity and the absence of standardized methods for characterizing vegetation traits. Addressing these challenges and refining the representation of wash-off process will enhance the VIDA model's utility in predicting the dynamic relationship between vegetation and air quality.The introduction of VIDA provides a significant advancement in modelling air pollution removal by deposition to vegetation at a relevant local scale and enables inclusion of urban greenery as tool in urban planning for air pollution mitigation.

Microalgae cultivation using ammonia and carbon dioxide concentrations typical of pig barns

ABSTRACT While global population growth drives increased production efficiency in animal agriculture, there is a growing demand for environmentally friendly practices, particularly in reducing air pollutant emissions from concentrated animal feeding operations. This study explores the potential of cultivating microalgae in photobioreactors (PBRs) as an eco-friendly and cost-effective approach to mitigate NH3 and CO2 emissions from pig barns. Unlike traditional physicochemical mitigation systems, microalgae offer a renewable solution by converting pollutants into valuable biomass. The research focused on Scenedesmus dimorphus growth under typical NH3 and CO2 concentrations found in the indoor air of pig barns. Four NH3 (0, 12, 25, and 50 ppm) and four CO2 concentrations (350, 1200, 2350, and 3500 ppm) were tested using photobioreactors. Results showed a maximum specific growth rate of 0.83 d−1 with 12 ppm NH3 and 3500 ppm CO2. The dry biomass concentration was significantly higher (1.16 ± 0.08 g L−1; p < 0.01) at 25 ppm NH3 and 2350 ppm CO2 than other test conditions. S. dimorphus demonstrated the peak NH3 and CO2 fixation rates (23.8 ± 2.26 mg NH3 L−1 d−1 and 432.24 ± 41.09 mg CO2 L−1 d−1) at 25 ppm NH3 and 2350 ppm CO2. These findings support the feasibility of using algae to effectively remove air pollutants in pig barns, thereby improving indoor air quality.