Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O₃, NO₂, NO, PM₂.₅, and PM₁₀, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

This review evaluates the three dynamic models (biokinetic model: BK, physiologically based pharmacokinetic model: PBPK, and toxicokinetic-toxicodynamic model: TKTD) in our understanding of the key questions in metal ecotoxicology in aquatic systems, i.e., bioaccumulation, transport and toxicity. All the models rely on the first-order kinetics principle of metal uptake and elimination. The BK model basically treats organisms as a single compartment, and is both physiologically and geochemically based. With a good understanding of each kinetic parameter, bioaccumulation of metals in any aquatic organisms can be studied holistically and mechanistically. Modeling efforts are not merely restrained from the prediction of metal accumulation in the tissues, but instead provide the direction of the key processes that need to be addressed. PBPK is more physiologically based since it mainly addresses the transportation, transformation and distribution of metals in the organisms. It can be treated conceptually as a multi-compartmental kinetic model, whereas the physiology is driving the development of any good PBPK model which is no generic for aquatic animals and contaminants. There are now increasingly applications of the PBPK modeling specifically in metal studies, which reveal many important processes that are impossible to be teased out by direct experimental measurements without adequate modeling. TKTD models further focus on metal toxicity in addition to metal bioaccumulation. The TK part links exposure and bioaccumulation, while the TD part links bioaccumulation and toxic effects. The separation of TK and TD makes it possible to model processes, e.g., toxicity modification by environmental factors, interaction between different metals, at both the toxicokinetic and toxicodynamic levels. TKTD models provide a framework for making full use of metal toxicity data, and thus provide more information for environmental risk assessments. Overall, the three models reviewed here will continue to provide guiding principles in our further studies of metal bioaccumulation and toxicity in aquatic organisms.

Floods are threats to ecosystems that are caused by natural disasters such as typhoons and heavy rain, and to respond to these threats, resilience needs to be improved. In this study, the response of the social-ecological system of Haeundae-gu (Busan, Republic of Korea) to disasters is analyzed by using a causal loop diagram, and a resilience improvement plan is presented by simulating the disaster resilience using green infrastructure through the System Resilience Dynamics Model. First, the resilience values are highest when green infrastructure is applied at the maximum applicable ratio (30%) compared with no application. Second, in the public and private areas of Haeundae-gu, resilience according to green roof scenario was higher until approximately 8 h after the beginning of rainfall, but then the resilience according to infiltration storage facility scenario was higher. In the transportation and industrial areas, the overall resilience according to infiltration storage facility scenario was higher than the resilience according to porous pavement scenario. This study demonstrates that a resilience improvement plan based on simulation can support decision making to respond to disasters such as typhoons.

Simulation modelling with CHUM-AM was carried out to investigate the accumulation and release of atmospherically-deposited heavy metals (Ni, Cu, Zn, Cd and Pb) in six moorland catchments, five with organic-rich soils, one with calcareous brown earths, in the Pennine chain of northern England. The model considers two soil layers and a third layer of weathering mineral matter, and operates on a yearly timestep, driven by deposition scenarios covering the period 1400-2010. The principal processes controlling heavy metals are competitive solid-solution partitioning of solutes, chemical interactions in solution, and chemical weathering. Agreement between observed and simulated soil metal pools and surface water concentrations for recent years was generally satisfactory, the results confirming that most contemporary soil metal is from atmospheric pollution. Metals in catchments with organic-rich soils show some mobility, especially under more acid conditions, but the calcareous mineral soils have retained nearly all anthropogenic metal inputs. Complexation by dissolved organic matter and co-transport accounts for up to 80% of the Cu in surface waters.

17β-estradiol (E2) often coexists with tetracyclines (TCs) in wastewater lagoons at intensive breeding farms, threatening the quality of surrounding water bodies. Microbial degradation is vital in E2 removal, but it is unclear how TCs affect E2 biodegradation. This primary study investigated the mechanisms of E2 degradation by Novosphingobium sp. ES2-1 in the presence of TCs and assessed the removal efficiency of E2 by strain ES2-1 in natural waters containing TCs. E2 biodegradation was unaffected at TCs concentrations below 0.1 mg L⁻¹ yet significantly inhibited at TCs above 10 mg L⁻¹. As elevation of TCs, E2 biodegradation rate constant decreased, and the biodegradation kinetics equation gradually deviated from the pseudo-first-order dynamics model. Importantly, the presence of TCs, especially at high-level concentrations, significantly hindered E2 ring-opening process but promoted the condensation of some phenolic ring-opening products with NH₃, thereby increasing the abundance of pyridine derivatives, which were difficult to decompose over time. Additionally, strain ES2-1 could remove 52.1–100% of nature estrogens in TCs-contaminated natural waters within 7 d. Results revealed the mechanisms of TCs in E2 biodegradation and the performance of a functional strain in estrogen removal in realistic TCs-contaminated aqueous solution.

China is now experiencing major public health challenges caused by air pollution. Few studies have quantified the dynamics of air pollution and its impact on the risk of respiratory infection. We conducted an integrated data analysis to quantify the association among air quality index (AQI), meteorological variables and respiratory infection risk in Shaanxi province of China in the period of November 15th, 2010 to November 14th, 2016. Our analysis illustrated a statistically significantly positive correlation between the number of influenza-like illness (ILI) cases and AQI, and the respiratory infection risk has increased progressively with increased AQI with a time lag of 0–3 days. We also developed mathematical models for the AQI trend and respiratory infection dynamics, incorporating AQI-dependent incidence and AQI-based behaviour change interventions. Our combined data and modelling analysis estimated the basic reproduction number for the respiratory infection during the studying period to be 2.4076, higher than the basic reproduction number of the 2009 pandemic influenza in the same province. Our modelling-based simulations concluded that, in terms of respiratory infection risk reduction, the persistent control of emission in the China's blue-sky programme is much more effective than substantial social-economic interventions implemented only during the smog days.

Coastal areas provide important ecosystem services and affect local tourism. However, these areas are also sensitive to coastal erosion. The purpose of this study was to simulate a landscape plan scenario to improve the value of ecosystem services. The Shinduri coastal area in South Korea which has important natural resources, such as coastal sand dunes and coastal forests. To simulate landscape changes, this study was conducted using system dynamics. The study progressed in three stages: first, an analysis of the landscape change behavior model of Shinduri in its current state and an evaluation of the value of ecosystem services was conducted. Second, a simulation was carried out by applying a coastal erosion scenario. Third, a simulation of landscape change was run, and the value of ecosystem services was estimated, with regard to afforestation, thinning, weeding and coastal sand dune restoration plan scenarios. The results were as follows: in the absence of disturbances, current landscape change models are stable, and the value of ecosystem services, which was $859,259 in 2014, has increased over time. However, the value of ecosystem services decreased when subjected to a coastal erosion scenario. The evaluation of value of ecosystem services under afforestation, thinning, weeding and coastal sand dune plan scenarios revealed an optimal landscape plan that focuses on a coastal sand dune restoration plan suggesting restoration of these dunes at a rate of 27.05 ha per year. When the coastal sand dune restoration plan is applied, the value of ecosystem services increases to $ 895,474 by 2054. The coastal sand dune restoration plan should prioritize the protection of the coastal sand dune area as component of the restoration of coastal ecological resources in the area. These findings could contribute to the ecological management and improvement of coastal ecosystem services.

Hazard assessment of chemical contaminants often relies on short term or partial life-cycle ecotoxicological tests, while the impact of low dose throughout the entire life cycle of species across multiple generations has been neglected. This study aimed at identifying the individual and population-level consequences of chronic water contamination by environmental concentrations of three organic micropollutants, ibuprofen, bisphenol A and benzo[a]pyrene, on Aedes aegypti mosquito populations in experimental conditions. Life-history assays spanning the full life-cycle of exposed individuals and their progeny associated with population dynamics modelling evidenced life-history traits alterations in unexposed progenies of individuals chronically exposed to 1 μg/L ibuprofen or 0.6 μg/L benzo[a]pyrene. The progeny of individuals exposed to ibuprofen showed an accelerated development while the progeny of individuals exposed to benzo[a]pyrene showed a developmental acceleration associated with an increase in mortality rate during development. These life-history changes due to pollutants exposure resulted in relatively shallow increase of Ae. aegypti asymptotic population growth rate. Multigenerational exposure for six generations revealed an evolution of population response to ibuprofen and benzo[a]pyrene across generations, leading to a loss of previously identified transgenerational effects and to the emergence of a tolerance to the bioinsecticide Bacillus turingiensis israelensis (Bti). This study shed light on the short and long term impact of environmentally relevant doses of ibuprofen and benzo[a]pyrene on Ae. aegypti life-history traits and insecticide tolerance, raising unprecedented perspectives about the influence of surface water pollution on vector-control strategies. Overall, our approach highlights the importance of considering the entire life cycle of organisms, and the necessity to assess the transgenerational effects of pollutants in ecotoxicological studies for ecological risk assessment. Finally, this multi-generational study gives new insight about the influence of surface water pollution on microevolutionary processes.

A spatially-explicit version of the recent multimedia fate model SoilPlus was developed and applied to predict the runoff of three pesticides in a small agricultural watershed in north-eastern Italy. In order to evaluate model response to increasing spatial resolution, a tiered simulation approach was adopted, also using a dynamic model for surface water (DynA model), to predict the fate of pesticides in runoff water and sediment, and concentrations in river water. Simulation outputs were compared to water concentrations measured in the basin. Results showed that a high spatial resolution and scenario complexity improved model predictions of metolachlor and terbuthylazine in runoff to an acceptable performance (R2 = 0.64–0.70). The importance was also shown of a field-based database of properties (i.e. soil texture and organic carbon, rainfall and water flow, pesticides half-life in soil) in reducing the distance between predicted and measured surface water concentrations and its relevance for risk assessment.

A dynamic model of forest ecosystems was used to investigate the effects of climate change, atmospheric deposition and harvest intensity on 48 forest sites in Sweden (n = 16) and Switzerland (n = 32). The model was used to investigate the feasibility of deriving critical loads for nitrogen (N) deposition based on changes in plant community composition. The simulations show that climate and atmospheric deposition have comparably important effects on N mobilization in the soil, as climate triggers the release of organically bound nitrogen stored in the soil during the elevated deposition period. Climate has the most important effect on plant community composition, underlining the fact that this cannot be ignored in future simulations of vegetation dynamics. Harvest intensity has comparatively little effect on the plant community in the long term, while it may be detrimental in the short term following cutting. This study shows: that critical loads of N deposition can be estimated using the plant community as an indicator; that future climatic changes must be taken into account; and that the definition of the reference deposition is critical for the outcome of this estimate.