Long-term investigation of methane and carbon dioxide emissions in two Italian landfills

Landfills play a key role as greenhouse gas (GHGs) emitters, and urgently need assessment and management plans development to swiftly reduce their climate impact. In this context, accurate emission measurements from landfills under different climate and management would reduce the uncertainty in emission accounting. In this study, more than one year of long-term high-frequency data of CO2 and CH4 fluxes were collected in two Italian landfills (Giugliano and Case Passerini) with contrasting management (gas recovery VS no management) using eddy covariance (EC), with the aim to i) investigate the relation between climate drivers and CO2 and CH4 fluxes at different time intervals and ii) to assess the overall GHG balances including the biogas extraction and energy recovery components. Results indicated a higher net atmospheric CO2 source (5.7 ± 5.3 g m2 d-1) at Giugliano compared to Case Passerini (2.4 ± 4.9 g m2 d-1) as well as one order of magnitude higher atmospheric CH4 fluxes (6.0 ± 5.7 g m2 d-1 and 0.7 ± 0.6 g m2 d-1 respectively). Statistical analysis highlighted that fluxes were mainly driven by thermal variables, followed by water availability, with their relative importance changing according to the time-interval considered. The rate of change in barometric pressure (dP/dt) influenced CH4 patterns and magnitude in the classes ranging from -1.25 to +1.25 Pa h-1, with reduction when dP/dt > 0 and increase when dP/dt < 0, whilst a clear pattern was not observed when all dP/dt classes were analyzed. When including management, the total atmospheric GHG balance computed for the two landfills of Giugliano and Case Passerini was 174 g m2 d-1 and 79 g m2 d-1 respectively, of which 168 g m2 d-1 and 20 g m2 d-1 constituted by CH4 fluxes.

Assessment of seasonal variations in particulate matter accumulation and elemental composition in urban tree species

Outdoor air pollution in urban areas, especially particulate matter (PM), is harmful to human health. Urban trees and shrubs provide crucial ecosystem services such as air pollution mitigation by acting as natural filters. However, urban greenery comprises a particular biodiversity, and different plant species vary in their capacity to accumulate PM. Twenty-two plant species were analyzed and selected according to their leaf traits, the different fractions of PM accumulated on the leaves (large - PML, coarse - PMC, and fine - PMF) and their chemical composition. The study was conducted in four city zones: urban traffic (UT), urban background (UB), industrial (IND), and rural (RUR), comparing winter (W) and summer (S) seasons. The average PM levels in the air and accumulated on the leaves were higher in W than in S season. During both seasons, the highest PM accumulated on the leaves was recorded at the UT zone. Nine species were selected as the most suitable for accumulating PML, seven as the most efficient for accumulating PMC, and six for accumulating PMF. The leaf area and leaf roundness were correlated negatively with PM accumulation. The evergreen species L. nobilis was indicated as suitable for dealing with air pollution based on PM10 and PM2.5 values recorded in the air. Regarding the PM element and metal composition, L. nobilis, Photinia x fraseri, Olea europaea, Quercus ilex and Nerium oleander were selected as species with notable elements and metal accumulation. In summary, the study identified species with higher PM accumulation capacity and assessed the seasonal PM accumulation patterns in different city zones, providing insights into the species interactions with PM and their potential for monitoring and coping with air pollution.

Correlation between microbial communities and volatile organic compounds in an urban soil provides clues on soil quality towards sustainability of city flowerbeds

Soil functionality is critical to the biosphere as it provides ecosystem services relevant for a healthy planet. The soil microbial composition is significantly impacted by anthropogenic activities, including urbanization. In this context, the study of soil microorganisms associated to urban green spaces has started to be crucial toward sustainable city development. Microbes living in the soil produce and degrade volatile organic compounds (VOCs). The VOC profiles may be used to distinguish between soils with various characteristics and management practices, reflecting variations in the activity of soil microbes that use a variety of metabolic pathways. Here, a combined approach based on DNA metabarcoding and GC-MS analysis was used to evaluate the soil quality from urban flowerbeds in Prato (Tuscany, Italy) in terms of microbial biodiversity and VOC emission profiles, with the final aim of evaluating the possible correlation between composition of microbial community and VOC patterns. Results showed that VOCs in the considered soil originated from anthropic and biological activity, and significant correlations between specific microbial taxa and VOCs were detected. Overall, the study demonstrated the feasibility of the use of microbe-VOC correlation as a proxy for soil quality assessment in urban soils.

An integrated approach to estimate how much urban afforestation can contribute to move towards carbon neutrality

Urban afforestation is considered a promising nature-climate solution that may contribute to achieve climate neutrality by 2050, since it can increase C-storage and C-sequestration, whilst providing further multiple ecosystem services for citizens. However, the quantification of the CO₂ sequestration capacity that may be provided by an urban forest as well as the capacity to impact the city-level C-balance and offset anthropogenic emissions is a complex issue. Methodological approaches, quantity and quality of information contained in urban tree database, and the level of detail of the planned urban forest can strongly influence the estimation of C-sequestration potential offered by urban forests. In this work, an integrated framework based on emission inventory, tree species/morphology and ecosystem modelling has been proposed for the city of Prato, Italy, a representative medium size European city to: i) evaluate the current C-sequestration capacity of urban trees; ii) upscale such capacity with different afforestation scenarios, iii) compare the sink capacity offered by ecosystems with current and projected anthropogenic emissions. Results indicated that the green areas within the Municipality of Prato can sequester 33.1 ktCO₂ yr^-1 under actual conditions and 51.0 ktCO₂ yr^-1 under the afforestation scenario which maximize the CO₂ sequestration capacity, offsetting the 7.1 % and 11 % of the total emissions (465.8 ktCO₂ yr^-1), respectively. This study proves that, in the various afforestation scenarios tested, the contribution of urban afforestation to the municipality carbon balance is negligible and that carbon neutrality can only be reached by the substantial decarbonization of emission sectors.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO₂ emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO₂, we analysed district level CO₂ fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO₂ emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO₂ emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

Unveiling the changes in urban atmospheric CO2 in the time of COVID-19 pandemic: A case study of Florence (Italy)

The outbreak of COVID-19 pandemic was accompanied by global mobility restrictions and slowdown in manufacturing activities. Accordingly, cities experienced a significant decrease of CO₂ emissions. In this study, continuous measurements of CO₂ fluxes, atmospheric CO₂ concentrations and δ¹³C-CO₂ values were performed in the historical center of Florence (Italy) before, during and after the almost two-month long national lockdown. The temporal trends of the analyzed parameters, combined with the variations in emitting source categories (from inventory data), evidenced a fast response of flux measurements to variations in the strength of the emitting sources. Similarly, the δ¹³C-CO₂ values recorded the change in the prevailing sources contributing to urban atmospheric CO₂, confirming the effectiveness of carbon isotopic data as geochemical tracers for identifying and quantifying the relative contributions of emitting sources. Although the direct impact of restriction measurements on CO₂ concentrations was less clear due to seasonal trends and background fluctuations, an in-depth analysis of the daily local CO₂ enhancement with respect to the background values revealed a progressive decrease throughout the lockdown phase at the end of the heating season (>10 ppm), followed by a net increase (ca. 5 ppm) with the resumption of traffic. Finally, the investigation of the shape of the frequency distribution of the analyzed variables revealed interesting aspects concerning the dynamics of the systems.

The role of emissions and meteorology in driving CO2 concentrations in urban areas

A multi-year dataset of measurements of CO₂ concentrations, eddy covariance fluxes, and meteorological parameters over the city centre of Florence (Italy) has been analysed to assess the role of anthropogenic emissions and meteorology in controlling urban CO₂ concentrations. The latter exhibited a negative correlation with air temperature, wind speed, solar radiation, and sensible heat flux and a positive one with relative humidity and emissions. A linear and an artificial neural network (ANN) model have been developed and validated for short-term modelling of 3-h CO₂ concentrations. The ANN model performed better, with mean bias of 0.58 ppm, root mean square error within 30 ppm, and r²=0.49. Data clustering through the self-organized maps allowed to disentangle the role played by emissions and meteorological parameters in influencing CO₂ concentrations. Sensitivity analysis of CO₂ concentrations revealed a primary role played by the meteorological parameters, particularly wind speed. These results highlighted that (i) emission reduction actions at local urban scale should be better tied to actual and expected meteorological conditions and (ii) those actions alone have limited effects (e.g. a 20% emission reduction would result in a 3% CO₂ concentrations reduction). For all these reasons, large-scale policies would be needed.

Quantifying road traffic impact on air quality in urban areas: A Covid19-induced lockdown analysis in Italy

Covid19-induced lockdown measures caused modifications in atmospheric pollutant and greenhouse gas emissions. Urban road traffic was the most impacted, with 48-60% average reduction in Italy. This offered an unprecedented opportunity to assess how a prolonged (∼2 months) and remarkable abatement of traffic emissions impacted on urban air quality. Six out of the eight most populated cities in Italy with different climatic conditions were analysed: Milan, Bologna, Florence, Rome, Naples, and Palermo. The selected scenario (24/02/2020-30/04/2020) was compared to a meteorologically comparable scenario in 2019 (25/02/2019-02/05/2019). NO₂, O₃, PM_2.5 and PM₁₀ observations from 58 air quality and meteorological stations were used, while traffic mobility was derived from municipality-scale big data. NO₂ levels remarkably dropped over all urban areas (from -24.9% in Milan to -59.1% in Naples), to an extent roughly proportional but lower than traffic reduction. Conversely, O₃ concentrations remained unchanged or even increased (up to 13.7% in Palermo and 14.7% in Rome), likely because of the reduced O₃ titration triggered by lower NO emissions from vehicles, and lower NO_x emissions over typical VOCs-limited environments such as urban areas, not compensated by comparable VOCs emissions reductions. PM₁₀ exhibited reductions up to 31.5% (Palermo) and increases up to 7.3% (Naples), while PM_2.5 showed reductions of ∼13-17% counterbalanced by increases up to ∼9%. Higher household heating usage (+16-19% in March), also driven by colder weather conditions than 2019 (-0.2 to -0.8 °C) may partly explain primary PM emissions increase, while an increase in agriculture activities may account for the NH₃ emissions increase leading to secondary aerosol formation. This study confirmed the complex nature of atmospheric pollution even when a major emission source is clearly isolated and controlled, and the need for consistent decarbonisation efforts across all emission sectors to really improve air quality and public health.

Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m-3 for PM2.5 and ≈3 µg m-3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m-3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

Seasonal and diurnal variations of greenhouse gases in Florence (Italy): Inferring sources and sinks from carbon isotopic ratios

In this study, the results of a continuous monitoring of (i) CO₂ fluxes, and (ii) CO₂ and CH₄ concentrations and carbon isotopic ratios (δ¹³C-CO₂ and δ¹³C-CH₄) in air, carried out from 7 to 21 July 2017 and from October 10 to December 15, 2017 in the city centre of Florence, are presented. The measurements were performed from the roof of the historical building of the Ximenes Observatory. CO₂ flux data revealed that the metropolitan area acted as a net source of CO₂ during the whole observation period. According to the Keeling plot analysis, anthropogenic contributions to atmospheric CO₂ were mainly represented by vehicular traffic (about 30%) and natural gas combustion (about 70%), the latter contributing 7 times more in December than in July. Moreover, the measured CO₂ fluxes were about 80% higher in fall than in summer, confirming that domestic heating based on natural gas is the dominant CO₂ emitting source in the municipality of Florence. Even though the continuous monitoring revealed a shift in the δ¹³C-CO₂ values related to photosynthetic uptake of atmospheric CO₂, the isotopic effect induced by plant activity was restricted to few hours in October and, to a lesser extent, in November. This suggests that urban planning policies should be devoted to massively increase green infrastructures in the metropolitan area in order to counterbalance anthropogenic emissions. During fall, the atmospheric CH₄ concentrations were sensibly higher with respect to those recorded in summer, whilst the δ¹³C-CH₄ values shifted towards heavier values. The Keeling plot analysis suggested that urban CH₄ emissions were largely related to fugitive emissions from the natural gas distribution pipeline network. On the other hand, δ¹³C-CH₄ monitoring allowed to recognize vehicular traffic as a minor CH₄ emitting source.

Locating and quantifying multiple landfills methane emissions using aircraft data

A mass balance approach to quantify methane (CH4) emission of four co-located landfills by means of airborne measurements and dispersion modelling was proposed and assessed. By flying grids at different heights above the landfills, atmospheric CH4 densities and wind components were measured along the edges and inside the study atmospheric volume, in order to calculate mass flows in the along- and across-wind directions. A steady-state Gaussian dispersion model was applied to build the concentration fields associated to unit emission from each landfill, while the contribution of each one to the total emission was assessed using a General Linear Model approach, minimizing the difference between measured and modeled mass flows. Results showed that wind spatial and temporal variability is the main factor controlling the accuracy of the method, as a good agreement between measured and modeled mass flows was mainly found for flights made in steady wind conditions. CH4 emissions of the entire area ranged from 213.5 ± 33.5 to 317.9 ± 90.4 g s-1 with a mean value of 252.5 ± 54.2 g s-1. Contributions from individual sources varied from 17.5 to 40.1 g m-2 day-1 indicating a substantial heterogeneity of the different landfills, which differed in age and waste composition. The proposed method was validated against tower eddy covariance flux measurements made at one of the landfills, revealing an overall agreement within 20%.

Composition and emission of VOC from biogas produced by illegally managed waste landfills in Giugliano (Campania, Italy) and potential impact on the local population

The composition in Volatile Organic Compounds (VOC) of the biogas produced by seven landfills of Giugliano (Naples, Campania, Italy) was determined and VOC emission rates assessed to verify if these compounds represent a potential threat to the population living nearby. VOC composition in the biogas could not be predicted, as heterogeneous waste was dumped from the late 1980s to the early 2000s and then underwent biological degradation. No data are available on the amount and composition of VOC in the biogas before the landfills closure as no operational biogas collection system was present. In this study, VOC composition was determined by gas chromatography-mass spectrometry (GC-MS), after collecting samples from collection pipes and from soil fractures in cover soil or capping. Individual VOC were quantified and data compared with those collected at two landfills in Latium, when they were still in operation. Relevant differences were observed, mainly due to waste aging, but no specific VOC revealing toxic waste dumping was found, although the concurrent presence of certain compounds suggested that dumping of industrial wastes might have occurred. The average VOC emission was assessed and a dispersion model was run to find out if the emitted plume could affect the health of population. The results suggested that fugitive emissions did not represent a serious danger, since the concentrations simulated at the neighboring cities were below the threshold limits for acute and chronic diseases. However, VOC plume could cause annoyance at night when the steady state conditions of the atmosphere enhance pollutants accumulation in the lower layers. In addition, some of the emitted VOC, such as alkylbenzenes and monoterpenes, can contribute to tropospheric ozone formation.

Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors

A low-cost air quality station has been developed for real-time monitoring of main atmospheric pollutants. Sensors for CO, CO₂, NO₂, O₃, VOC, PM2.5 and PM10 were integrated on an Arduino Shield compatible board. As concerns PM2.5 and PM10 sensors, the station underwent a laboratory calibration and later a field validation. Laboratory calibration has been carried out at the headquarters of CNR-IBIMET in Florence (Italy) against a TSI DustTrak reference instrument. A MATLAB procedure, implementing advanced mathematical techniques to detect possible complex non-linear relationships between sensor signals and reference data, has been developed and implemented to accomplish the laboratory calibration. Field validation has been performed across a full "heating season" (1 November 2016 to 15 April 2017) by co-locating the station at a road site in Florence where an official fixed air quality station was in operation. Both calibration and validation processes returned fine scores, in most cases better than those achieved for similar systems in the literature. During field validation, in particular, for PM2.5 and PM10 mean biases of 0.036 and 0.598 µg/m³, RMSE of 4.056 and 6.084 µg/m³, and R² of 0.909 and 0.957 were achieved, respectively. Robustness of the developed station, seamless deployed through a five and a half month outdoor campaign without registering sensor failures or drifts, is a further key point.

Influence of road traffic, residential heating and meteorological conditions on PM10 concentrations during air pollution critical episodes

The importance of road traffic, residential heating and meteorological conditions as major drivers of urban PM10 concentrations during air pollution critical episodes has been assessed in the city of Florence (Italy) during the winter season. The most significant meteorological variables (wind speed and atmospheric stability) explained 80.5-85.5% of PM10 concentrations variance, while a marginal role was played by major emission sources such as residential heating (12.1%) and road traffic (5.7%). The persistence of low wind speeds and unstable atmospheric conditions was the leading factor controlling PM10 during critical episodes. A specific PM10 critical episode was analysed, following a snowstorm that caused a "natural" scenario of 2-day dramatic road traffic abatement (-43%), and a massive (up to +48%) and persistent (8 consecutive days) increase in residential heating use. Even with such a strong variability in local PM10 emissions, the role of meteorological conditions was prominent, revealing that short-term traffic restrictions are insufficient countermeasures to reduce the health impacts and risks of PM10 critical episodes, while efforts should be made to anticipate those measures by linking them with air quality and weather forecasts.

Methane and carbon dioxide fluxes and source partitioning in urban areas: the case study of Florence, Italy

Long-term fluxes of CO(2), and combined short-term fluxes of CH(4) and CO(2) were measured with the eddy covariance technique in the city centre of Florence. CO(2) long-term weekly fluxes exhibit a high seasonality, ranging from 39 to 172% of the mean annual value in summer and winter respectively, while CH(4) fluxes are relevant and don't exhibit temporal variability. Contribution of road traffic and domestic heating has been estimated through multi-regression models combined with inventorial traffic and CH(4) consumption data, revealing that heating accounts for more than 80% of observed CO(2) fluxes. Those two components are instead responsible for only 14% of observed CH(4) fluxes, while the major residual part is likely dominated by gas network leakages. CH(4) fluxes expressed as CO(2) equivalent represent about 8% of CO(2) emissions, ranging from 16% in summer to 4% in winter, and cannot therefore be neglected when assessing greenhouse impact of cities.

Locating industrial VOC sources with aircraft observations

Observation and characterization of environmental pollution, focussing on Volatile Organic Compounds (VOCs), in a high-risk industrial area, are particularly important in order to provide indications on a safe level of exposure, indicate eventual priorities and advise on policy interventions. The aim of this study is to use the Solid Phase Micro Extraction (SPME) method to measure VOCs, directly coupled with atmospheric measurements taken on a small aircraft environmental platform, to evaluate and locate the presence of VOC emission sources in the Marghera industrial area. Lab analysis of collected SPME fibres and subsequent analysis of mass spectrum and chromatograms in Scan Mode allowed the detection of a wide range of VOCs. The combination of this information during the monitoring campaign allowed a model (Gaussian Plume) to be implemented that estimates the localization of emission sources on the ground.

Carbon dioxide and acetone air-sea fluxes over the southern Atlantic

Measurements of CO2 and acetone fluxes have been made over a large-scale, naturally occurring high latitude phytoplankton bloom in the remote South Atlantic. Shipborne micrometeorological methods for direct atmospheric flux measurement have been applied to determine the direction and size of the CO2 and acetone fluxes. Previous results suggest that high latitude oligotrophic ocean regions are sinks of acetone, whereas high productivity regions are sources. The observed CO2 fluxes are into the ocean and on the order of 1 micromol m(-2) s(-1) at most. The acetone fluxes measured show a significant relationship with chlorophyll in the region of the phytoplankton bloom. Although the uncertainty is very high due to the very low signal-to-noise ratio, significant positive acetone mean fluxes of the order of 0.01 nmol m(-2) s(-1) have been observed in bloom areas, whereas near zero, negative, or highly variable low acetone fluxes have been measured elsewhere. Based on these results we estimate that the global acetone source from bloom affected areas is small in comparison to the uptake from the much larger oligotrophic regions, and that the ocean is globally a net sink for acetone.