Status, sources and contamination levels of organochlorine pesticide residues in urban and agricultural areas: a preliminary review in central–southern Italian soils

Organochlorine pesticides (OCPs) are synthetic chemicals commonly used in agricultural activities to kill pests and are persistent organic pollutants (POPs). They can be detected in different environmental media, but soil is considered an important reservoir due to its retention capacity. Many different types of OCPs exist, which can have different origins and pathways in the environment. It is therefore important to study their distribution and behaviour in the environment, starting to build a picture of the potential human health risk in different contexts. This study aimed at investigating the regional distribution, possible sources and contamination levels of 24 OCP compounds in urban and rural soils from central and southern Italy. One hundred and forty-eight topsoil samples (0–20 cm top layer) from 78 urban and 70 rural areas in 11 administrative regions were collected and analysed by gas chromatography–electron capture detector (GC–ECD). Total OCP residues in soils ranged from nd (no detected) to 1043 ng/g with a mean of 29.91 ng/g and from nd to 1914 ng/g with a mean of 60.16 ng/g in urban and rural area, respectively. Endosulfan was the prevailing OCP in urban areas, followed by DDTs, Drins, Methoxychlor, HCHs, Chlordane-related compounds and HCB. In rural areas, the order of concentrations was Drins > DDTs > Methoxychlor > Endosulfans > HCHs > Chlordanes > HCB. Diagnostic ratios and robust multivariate analyses revealed that DDT in soils could be related to historical application, whilst (illegal) use of technical DDT or dicofol may still occur in some urban areas. HCH residues could be related to both historical use and recent application, whilst there was evidence that modest (yet significant) application of commercial technical HCH may still be happening in urban areas. Drins and Chlordane compounds appeared to be mostly related to historical application, whilst Endosulfan presented a complex mix of results, indicating mainly historical origin in rural areas as well as potential recent applications on urban areas. Contamination levels were quantified by Soil Quality Index (SoQI), identifying high levels in rural areas of Campania and Apulia, possibly due to the intensive nature of some agricultural practices in those regions (e.g., vineyards and olive plantations). The results from this study (which is in progress in the remaining regions of Italy) will provide an invaluable baseline for OCP distribution in Italy and a powerful argument for follow-up studies in contaminated areas. It is also hoped that similar studies will eventually constitute enough evidence to push towards an institutional response for more adequate regulation as well as a full ratification of the Stockholm Convention

The consolidated European synthesis of CH₄ and N₂O emissions for the European Union and United Kingdom: 1990–2019

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH₄ and N₂O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH₄ emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH₄ yrc (EDGARv6.0, last year 2018) and 18.4 Tg CH₄ yr⁻¹ (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH₄ yr⁻¹. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH₄ yr⁻¹. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH₄ yr⁻¹ inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH₄ yr⁻¹. For N₂O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N₂O yr⁻¹, close to the NGHGI data (0.8±55 % Tg N₂O yr⁻¹). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N₂O yr⁻¹ (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH₄ and N₂O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH₄ and N₂O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH₄ and N₂O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH₄, N₂O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023)