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Food production has a profound eutrophication impact on waterbodies via nutrient leaching. To provide reliable life cycle assessments of the eutrophication potential of agricultural products, accurate nitrogen leaching models are needed. Although many dynamic nitrogen leaching models are in use, their suitability for farm-level assessments remains limited when their requirements for site specific data or numerous parameters are not met. In Finland, less data intensive leaching models for life cycle assessments have been developed using data from conventional farming, however, the suitability of these models for organic farming remains unknown. In this work, we developed new nitrogen leaching models that are applicable to both conventional and organic production. While this paper does not aim to argue in favor of organic or conventional farming it provides tools that can be used to inform decisions about management practices from the environmental perspective. We utilized up to 16 years of field measurements from two leaching fields in Finland. We developed prediction equations for nitrogen leaching for two soil types: sand soil and clay soil. According to our statistical analysis based on the data, the relevant factors for explaining nitrogen leaching included soil type, rainfall, whether the farming is done organically, and the availability of nitrogen for leaching. Computed nitrogen balance as such was found to be a poor proxy for nitrogen available for leaching, while nitrate nitrogen concentration measurement of the soil carried out in the fall was found to be a valuable predictor. Organic farming, with a crop rotation resembling that of conventional farming, resulted on average in 20% less nitrogen leached per hectare as compared to conventional farming with 95% C.I. [-34%, -3%]. The developed models are suitable for integration into a life cycle assessment framework, and especially the models utilizing nitrate nitrogen were shown to be applicable to a wide range of different crop types, making the model well-suited for plots with diverse crop rotations., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: financial support was provided by Business Finland., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NO x ), and black carbon (BC). CO and NO x are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NO x , and carbon dioxide (CO 2 ) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO 2 , ΔNO x /ΔCO, ΔNO x /ΔCO 2 , and ΔCO/ΔCO 2 ), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO 2 , ΔNO x /ΔCO 2 , and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NO x emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Elsevier Ltd. All rights reserved.)

Surface water pollution with poly- and perfluorinated compounds (PFAS) is a well-recognized problem, but knowledge about contribution of different emission pathways, especially diffuse ones, is very limited. This study investigates the potential of the pathway oriented MoRE model in shedding light on the relevance of different emission pathways on regional scale and in predicting concentrations and loads in unmonitored rivers. Modelling was supported with a tailor-made monitoring programme aimed to fill gaps on PFAS concentration in different environmental compartments. The study area covers the whole Austrian territory including some additional transboundary catchments and it focuses on perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). These two PFAS are regulated and therefore their production and use in Europe are currently decreasing. Nevertheless, these compounds are still emitted into the environment via legacy pollution and as transformation products from other PFAS. These two compounds were selected for this study in view of the larger information availability compared to other PFAS. Despite considerable uncertainties in the input data, model validations show that this approach performs significantly better than previous modelling frameworks based on population-specific emission factors, population density and wastewater treatment plant information. The study reveals the predominance of emissions via municipal wastewater treatment plants for PFOS and a relevant role of diffuse emission pathways for PFOA. Results suggest that unpaved areas contribute the biggest share to total diffuse emissions, but the estimation of these pathways is affected by the highest uncertainty in the input data and requires better input data from monitoring. Once the currently growing substance-specific data sets on the concentration of PFAS, others than PFOS and PFOA, in different environmental compartments, will reach an adequate quality, the model presented here will be easily applicable to them., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Plant cuticles are a mixture of crystalline and amorphous waxes that restrict the exchange of molecules between the plant and the atmosphere. The multicomponent nature of cuticular waxes complicates the study of the relationship between the physical and transport properties. Here, a model cuticle based on the epicuticular waxes of Petunia hybrida flower petals was formulated to test the effect of wax composition on diffusion of water and volatile organic compounds (VOCs). The model cuticle was composed of an n-tetracosane (C 24 H 50 ), 1-docosanol (C 22 H 45 OH), and 3-methylbutyl dodecanoate (C 17 H 34 O 2 ), reflecting the relative chain length, functional groups, molecular arrangements, and crystallinity of the natural waxes. Molecular dynamics simulations were performed to obtain diffusion coefficients for compounds moving through waxes of varying composition. Simulated VOC diffusivities of the model system were found to highly correlate with in vitro measurements in isolated petunia cuticles. VOC diffusivity increased up to 30-fold in completely amorphous waxes, indicating a significant effect of crystallinity on cuticular permeability. The crystallinity of the waxes was highly dependent on the elongation of the lattice length and decrease in gap width between crystalline unit cells. Diffusion of water and higher molecular weight VOCs were significantly affected by alterations in crystalline spacing and lengths, whereas the low molecular weight VOCs were less affected. Comparison of measured diffusion coefficients from atomistic simulations and emissions from petunia flowers indicates that the role of the plant cuticle in the VOC emission network is attributed to the differential control on mass transfer of individual VOCs by controlling the composition, amount, and dynamics of scent emission., (© 2022 Society for Experimental Biology and John Wiley & Sons Ltd.)

Characterized by a high frequency of use, harsh working environments, poor maintenance, and low levels of emission controls, rural vehicles (RVs) are becoming an important source of air pollution. Our study used a portable emission measurement system (PEMS) to test the real-world emissions of 35 RVs on provincial, rural, and farm roads. The results show that high emission rates of carbon monoxide (CO) and hydrocarbons (HC) mainly occurred when accelerating at low speeds. However, high levels of nitrogen oxides (NO x ) were emitted during high-speed acceleration. The particulate number (PN) of emissions was higher when the RVs were accelerating. According to the overall test results, the vehicle specific power (VSP) on the provincial road mostly ranged within (0, 3], accounting for 68.80% of the total. The VSP on rural and farm roads was concentrated within (0, 2] kW·ton -1 , accounting for 67.09% and 76.64% of the total, respectively. We defined 14 bins based on the distribution of the VSP values and calculated the average emission rate of each bin. By comparing the average emission rate among the bins, we found that within Bins 1-7 (VSP < 0 kW·ton -1 ), CO, HC, and NO x emissions slowly increased as the VSP increased. In Bins 8-13 (VSP ≥ 0 kW·ton -1 ), the average emission rates of four pollutants increased as the VSP increased. However, all pollutants decreased in Bin 14 (VSP ≥ 6 kW·ton -1 ). We built a microscopic emission model according to the VSP distribution characteristics of RVs on different road types. We compared the measured and simulated emission factors and found that our emission model can greatly simulate the HC, NOx and PN emission factors of RVs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Atmospheric emissions from passive liquid surfaces, such as wastewater treatment plants (WWTP), are common sources of impacts to the environment and to the health of communities, due to odours, greenhouse gases and other air pollutants. Emission models have been broadly employed for assessing these emissions, with the wind friction velocity (u ∗ ) being a key variable. The usual practice in the context of WWTP is to parametrise u ∗ based on reference wind speeds measured over the land, without considering the internal boundary layer (IBL) development due to the change in aerodynamic roughness as the wind blows from the land to the liquid surface, nor the stability of the wind flow. The potential consequences of these conceptual inconsistencies are major knowledge gaps in emission modelling. Addressing these, a customised computation was implemented to couple the wind friction parametrisation with the evolution of the IBL downwind of the land-to-water roughness change. A sensitivity analysis with different emission models, considering ranges of fetch, wind speed and surface roughness encompassing typical conditions in WWTP, showed that not incorporating the roughness change leads to systematic overestimation of u ∗ and the overall mass transfer coefficient K L for two compounds analysed (liquid phase and gas phase-controlled volatilisation). A modelling approach was devised, comprising the u ∗ parametrisation that incorporate the roughness change combined with the Prata-Brutsaert emission model and alternative calculation of the gas-side mass transfer coefficient k G from local IBL variables. Evaluation against experimental data and physical considerations support the adoption of this approach for modelling the volatilisation of compounds from passive liquid surfaces in WWTP. A simplified equation to approximate u ∗ after a change in roughness is presented, which can be used for quick emission modelling of liquid phase-controlled compounds. Furthermore, a preliminary exploration demonstrated that the effects of atmospheric stability on the response of u ∗ to the land-to-water roughness change can be substantial under certain conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This study developed a platform using a modelling and web technology approach to estimate methane emissions from landfills to assess methane emissions across the region. The web technology-based software EnLandFill, which was developed, allows users to log in, interact with landfill databases, and document and extract information regarding landfill emissions. Models that integrate web technology with databases and geographic information systems (GIS) are described. One of the achievements of this study was the development of an inverse algorithm to determine the waste source capacity according to a dispersion model, accounting for complex terrain and meteorological time-series data extracted from the Weather Research and Forecasting (WRF) model. EnLandFill software was applied to quantify CH 4 emissions for key developing regions, predicting approximately 158,977 tonnes, equivalent to 167,786,878 m 3 of CH 4 for the period of 2019 - 2030. The software also allows the evaluation of the scope and level of impacts of landfill emissions under given meteorological conditions., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This article proposes a methodology for the estimation of emissions in real driving conditions, based on board diagnostics data and machine learning, since it has been detected that there are no models for estimating pollutants without large measurement campaigns. For this purpose, driving data are obtained by means of a data logger and emissions through a portable emissions measurement system in a real driving emissions test. The data obtained are used to train artificial neural networks that estimate emissions, having previously estimated the relative importance of variables through random forest techniques. Then, by the application of the K-means algorithm, labels are obtained to implement a classification tree and thereby determine the selected gear by the driver. These models were loaded with a data set generated covering 1218.19 km of driving. The results generated were compared to the ones obtained by applying the international vehicle emissions model and with the results of the real driving emissions test, showing evidence of similar results. The main contribution of this article is that the generated model is stronger in different traffic conditions and presents good results at the speed interval with small differences at low average driving speeds because more than half of the vehicle's trip occurs in urban areas, in completely random driving conditions. These results can be useful for the estimation of emission factors with potential application in vehicular homologation processes and the estimation of vehicular emission inventories.

Soil can be resuspended in the atmosphere due to wind or mechanical disturbances, such as agricultural activities (sowing, tilling, etc.), producing fine particulate matter (PM). Agriculture is estimated to be the third PM 10 -emitting sector in Europe, emitting more than the transportation sector. However, very few emission figures are available for the different cropping operations. Moreover, soil Emission Potential (EP) is extremely variable, since is influenced by factors such as humidity, texture, chemical composition, and wind speed. Due to their similarity to tilling emission mechanisms, Soil Resuspension Chambers (SRC) are the most suitable method to estimate the impacts of these factors on soil susceptibility to emit PM 10 during cropping operations (Emission Potential, EP). The main objective of this work is to assess the EP of different agricultural soils used for maize cropping in North-Western Italy, studying the influence of soil moisture and physico-chemical characteristics. Therefore, a SRC was developed, based on previous studies, with the goal of being relatively small, easy to operate and low-cost. Using the gathered data, a log-linear multiple regression model was developed to allow soil EP estimation from few physico-chemical parameters (moisture, sand/silt ratio and organic carbon content). The model allows to tailor field Emission Factors (EF) of specific cropping operations to different soil and moisture conditions and was applied to an EF for rotary harrowing, defined in a previous study. The concentration of Potentially Toxic Elements (PTE) in soil-emitted PM 10 was determined, founding an enrichment up to 16 times higher than in the original soil, evidencing a possible cause of concern for operator's safety during agricultural activities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Urban wastewater treatment plants (WWTPs) can be an emission source of aerosol particles to the air and this process has the potential to spread emerging pollutants into the air, where the particles can be widely transported over long distances to areas where this pollution is unexpected. This study demonstrates aeration tanks in WWTPs as a potential source of ketamine, methamphetamine and other emerging contaminant emissions into the air. Ketamine and methamphetamine are frequently detected in high concentrations (maximum of 151.8-162.8 pg/m 3 ) in gaseous and aerosol samples along with 24 other emerging contaminants. Through correlation analysis, the common occurrence of emerging contaminants in air is attributable to their high aqueous concentrations as well as their physicochemical properties. Two simple regression models are developed to provide a practical and convenient way to estimate the steady-state concentrations in air. The gas-phase emission model illustrates the relationship between the solubility, the pK a and the aqueous concentration of compounds in the aeration basin and their gaseous concentrations in air (statistical strength of 74.1%; p value < 0.05), while the partition model establishes the ratio of a compound in the gas and particulate phases in air (statistical strength of 82.6%; p value < 0.05). The results provide a basis for assessing the risk of the inhalation exposure to airborne emerging contaminants; however, in-depth research addressing the impact of aerosols containing persistent pharmaceuticals on human health is still needed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The results of the research in the field of benzene, toluene, ethylbenzene and xylene isomers (BTEX) concentrations in exhaust gases of spark ignition engines under different operating conditions are presented in this paper. The aim of this paper is to gain a clearer insight into the impact of different engine working parameters on the concentrations of BTEX. The experimental investigation has been performed on the SCHENCK 230 W test stand with the controlled IC engine. The engine operating points have been chosen based on the results of a simulation and they are considered as the typical driving conditions according to the New European Driving Cycle. Concentration levels of BTEX compounds in exhaust gas mixtures have been determined by gas chromatography technique by using the combination of Supelcowax 10-Polyethylene glycol column and the PID detector. Based on the experimental research results, the emission model of BTEX compounds has been defined by the simulation of movement of a Fiat Punto Classic passenger car in accordance with the NEDC cycle. Using the results obtained within the simulation, the official statistics on the number of gasoline-powered cars on the territory of the Republic of Serbia and the European Commission data on the annual distance traveled by car, the amounts of BTEX compounds emitted annually per car have been estimated, as well as the emissions of the entire Serbian car fleet., (Copyright © 2018 Elsevier B.V. All rights reserved.)