Organic fraction municipal solid waste (OFMSW) has a high potential for energy and value-added product recovery due to its carbon- and nutrient-rich composition; however, traditional value chains have treated OFMSW as an undesired by-product. This study focuses on value chain optimisation to assist the transition to resource recovery value chains. To achieve this, this work combined two stage stochastic mathematical optimisation with geographical spatial analysis and time series waste generation analysis. Existing infrastructure in England, including anaerobic digestion plants and road transportation networks, were included in the model. To account for uncertainty in waste generation, multiple scenarios and their associated probabilities were developed based on environmental variables. The optimisation problem was solved to further advance the understanding of economically optimal waste-to-resource value chains under waste generation variability. The pertinent decision variables included sizing, technology selection, waste flows and location of thermochemical treatment sites. The model highlights the potential reduction in system profitability as a result of different operating constraints, such as minimum plant operating capacity factors and landfill taxation. The latter was shown to have the largest impact on profitability as overconservative systems designs were implemented to hedge against the waste variability. Such computer-aided models offer opportunities to overcome the challenges posed by waste generation variability and waste to resource value chain transformation.

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia’s most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series’ of nitrogen dioxide (NO₂), ozone (O₃), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM₂.₅), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM₂.₅ (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM₂.₅ 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6–343.) excess deaths and 3490.0 (95% CI 1325.9–5653.5) additional hospitalisations were likely as a result of PM₂.₅ and O₃ exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO₂ decreased by 21.5 and 8% in Victoria and NSW respectively. O₃ and PM₂.₅ remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.

On March 12th, 2020, the WHO declared COVID-19 as a pandemic. The collective impact of environmental and ecosystem factors, as well as biodiversity, on the spread of COVID-19 and its mortality evolution remain empirically unknown, particularly in regions with a wide ecosystem range. The aim of our study is to assess how those factors impact on the COVID-19 spread and mortality by country. This study compiled a global database merging WHO daily case reports with other publicly available measures from January 21st to May 18th, 2020. We applied spatio-temporal models to identify the influence of biodiversity, temperature, and precipitation and fitted generalized linear mixed models to identify the effects of environmental variables. Additionally, we used count time series to characterize the association between COVID-19 spread and air quality factors. All analyses were adjusted by social demographic, country-income level, and government policy intervention confounders, among 160 countries, globally. Our results reveal a statistically meaningful association between COVID-19 infection and several factors of interest at country and city levels such as the national biodiversity index, air quality, and pollutants elements (PM₁₀, PM₂.₅, and O₃). Particularly, there is a significant relationship of loss of biodiversity, high level of air pollutants, and diminished air quality with COVID-19 infection spread and mortality. Our findings provide an empirical foundation for future studies on the relationship between air quality variables, a country’s biodiversity, and COVID-19 transmission and mortality. The relationships measured in this study can be valuable when governments plan environmental and health policies, as alternative strategy to respond to new COVID-19 outbreaks and prevent future crises.

Detailed, high resolution time-series observations were performed to investigate sources, diel cycling, natural attenuation, and loadings of dissolved trace metals/metalloids in a subtropical headwater stream draining intensive horticulture in Australia. A transect of ∼3 km away from the source (farms) showed >75% reduction in concentration and loads of most trace elements. Mercury and arsenic had elevated loads downstream relative to other elements. Hourly time-series sampling revealed elevated creek discharge at night, accompanied by elevated nickel, selenium, copper, and mercury loads. Inputs from groundwater or treated sewage used for irrigation within the catchment are likely sources. Groundwater bore and treated sewage samples were highly contaminated with either zinc, copper, or mercury. Comparisons of daily and hourly samples indicated common sampling strategies can underestimate horticultural contaminant loadings. Load estimates for mercury and copper derived from hourly samples were 1.6- to 7- fold greater than loads from daily sample data collected over 79 days with varying rainfall. These high contaminant concentrations and loads are of concern to food products receiving irrigation and protected waterbodies downstream.

To determine whether natural recovery was occurring in a depositional area of the St. Marys River (Ontario, Canada) known as East Bellevue Marine Park (EBMP), sediment was collected from two depth ranges, 0–5 cm and 0–10 cm, and subjected to a series of laboratory toxicity tests and chemical analysis. Toxicological responses (survival, growth, reproduction, development) of four benthic invertebrates and the fathead minnow were compared at test vs. reference sites using univariate and multivariate (ordination) techniques. Temporal trends in sediment chemistry and invertebrate toxicity were examined with time series data from 2008 through to 2018. Polycyclic aromatic hydrocarbons (PAHs; ≤ 37 mg/kg) and petroleum hydrocarbons (PHCs; ≤ 6266 mg/kg) were elevated in EBMP compared to reference sites (PAHs, ≤ 1.6 mg/kg; PHCs ≤ 180 mg/kg). Comparatively, the 0–5 cm sediment layer had lower concentrations of all contaminants than the 0–10 cm layer at three of four test sites. Over time, contaminant concentrations have mostly remained stable or have decreased. There were no significant differences in survival, growth, or development of the larval fish in EBMP compared to the upstream reference sites, and no differences between sampling depths. However, most EBMP sediments were toxic to invertebrates, driven by reduced reproduction by the worm Tubifex and reduced survival by the amphipod Hyalella. Among habitat variables, a combination of different classes of compounds based on ordination scores (PHCs, oil and grease, metals) was most strongly correlated to toxicological response. There was little to no difference in toxicity between sampling depths based on integrated endpoint response; however, individual endpoints showed mostly greater toxicity from exposure to the 0–10 cm layer. Over time, toxicity has mostly remained stable or showed improvement. These results provided some positive indications that gradual natural recovery is occurring in EBMP.

The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM₂.₅) pollution associated with the COVID-19 lockdown has aroused great interest, but the estimation of the long-term health effects is difficult because of the lack of an annual mean air pollutant concentration under a whole-year lockdown scenario. We employed a time series decomposition method to predict the monthly PM₂.₅ concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM₂.₅ was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM₂.₅ concentrations in cites ranged from 5.4 to 68.0 μg m⁻³, and the national mean concentration was reduced by 32.2% compared to the 2015–2019 mean. The Global Exposure Mortality Model estimated that 837.3 (95% CI: 699.8–968.4) thousand people in Chinese cities would die prematurely from illnesses attributable to long-term exposure to ambient PM₂.₅. Compared to 2015–2019 mean levels, 140.2 (95% CI: 122.2–156.0) thousand premature deaths (14.4% of the annual mean deaths from 2015 to 2019) attributable to long-term exposure to PM₂.₅ were avoided. Because PM₂.₅ concentrations were still high under the whole-year lockdown scenario, the health benefit is limited, indicating that continuous emission-cutting efforts are required to reduce the health risks of air pollution. Since a similar scenario may be achieved through promotion of electric vehicles and the innovation of industrial technology in the future, the estimated long-term health impact under the whole year lockdown scenario can establish an emission–air quality–health impact linkage and provide guidance for future emission control strategies from a health protection perspective.

Coastal harmful algal blooms (HABs) in China’s seas have attracted researchers’ attention for decades. Among the four seas of China, the HAB frequency is the highest in the East China Sea (ECS). The impact of climate change and anthropogenic dominant factors on HABs is not well quantified and the response of HABs to the changing climate is also not clear. Here, we compiled a time series of observation-based HAB events since the 1980s and performed a regional assessment to elucidate the dominant drivers of HAB events in the ECS. The results showed that the increase in the frequency of HAB events in the ECS between 2000 and 2003 was associated with increases in dissolved inorganic phosphorus and sea surface temperature anomalies as well as decreasing summer precipitation. The declining annual frequency in HAB events in the ECS after 2003 was associated with the two climatological factors, most notably, precipitation. Under the “business-as-usual” scenario, climate change will increase the annual HAB events in the ECS from the historical frequency (1985–2013) by more than five-fold by the end of 21st century. These findings demonstrated that management strategies based on reducing nutrient loading also need to consider the effects of climate change in the future.

Groundwater chemistry can be affected by and related to earthquakes, thus it is crucial to understand the hydrochemical changes and associated processes caused by earthquakes for post-seismic groundwater utilization. Here we reported the major ion concentrations changes of the Ganze Spring in response to the May 30, 2014 Ms 6.1 Yingjiang earthquake, southwest China based on the daily time series (from 1st January 2012 to 20th July 2014) of Ca²⁺, Mg²⁺ and HCO₃⁻ concentrations, as well as data of bulk strain and Peak Ground Velocity (PGV) recorded at a nearby station. The results showed that the entire hydrochemical response process can be divided into two stages after the earthquake occurred: 1). decline stage which was characterized by an increasingly decline of the three ion concentrations, indicating a gradually significant dilution effect. At first, the relationship of molar concentrations of ions showed no obvious changes; but later as the rate of decrease in ion concentrations increased, the relationship between Ca²⁺ and HCO₃⁻ reversed from Ca²⁺ excess to HCO₃⁻ excess, probably resulting from a relatively decreased Ca²⁺ contribution from dissolution of gypsum and dolomite due to dilution in mixing water. 2). recover stage when the ion concentrations recovered gradually with relatively lower values than that at pre-earthquake, revealing the reduction of dilute water inflow. In combination with the bulk strain and PGV data, the study suggested that major ion concentrations changes are attributed to dilution effect due to new fracture creation or unclogging/clogging of fractures triggered by the earthquake. The results could enhance the understanding of earthquake induced water chemistry changes and could have implications for water resources management and security in tectonically active areas.

The influence of North African (NAF) dust events on the air quality at the regional level (12 representative monitoring stations) in Southern Europe during a long time series (2007–2014) was studied. PM10 levels and chemical composition were separated by Atlantic (ATL) and NAF air masses. An increase in the average PM10 concentrations was observed on sampling days with NAF dust influence (42 μg m⁻³) when compared to ATL air masses (29 μg m⁻³). Major compounds such as crustal components and secondary inorganic compounds (SIC), as well as toxic trace elements derived from industrial emissions, also showed higher concentrations of NAF events. A source contribution analysis using positive matrix factorisation (PMF) 5.0 of the PM10 chemical data, discriminating ATL and NAF air mass origins, allowed the identification of five sources: crustal, sea salt, traffic, regional, and industrial. A higher contribution (74%) of the natural sources to PM10 concentrations was confirmed under NAF episodes compared with ATL. Furthermore, there was an increase in anthropogenic sources during these events (51%), indicating the important influence of the NAF air masses on these sources. The results of this study highlight that environmental managers should take appropriate actions to reduce local emissions during NAF events to ensure good air quality.

Exposure to methylmercury (MeHg) through fish is a global public health problem. Exposure monitoring is essential for health risk assessment, especially in pregnant women and children due to the documented neurotoxicity. Herein, we evaluate a time series of MeHg exposure via fish in primiparous Swedish women, covering a time period of 23 years (1996–2019). The 655 included mothers were part of the POPUP study (Persistent Organic Pollutants in Uppsala Primiparas) conducted by the Swedish Food Agency (SFA). MeHg exposure was assessed via measurements of total mercury (Hg) in hair using either cold vapor atomic fluorescence spectrophotometry or inductively coupled plasma mass spectrometry, showing very good linear agreement (R² = 0.97). Maternal characteristics and fish consumption were obtained via questionnaires. The median concentration of total Hg in hair was 0.38 mg/kg (range 0.17–1.5) in 1996 and 0.25 mg/kg (range 0.03–1.1) in 2019. On average the women consumed 11 ± 8.2 meals of fish per month, and fish consumption was positively correlated with total Hg in hair (Spearman correlation: 0.39; p < 0.001). In multiple regression analyses, the geometric mean annual decrease of total Hg in hair was −2.5% (95% CI: -3.2, −1.8%). Total fish consumption increased up to 2011 (B: 0.32 times/month per year; 95% CI 0.17, 0.46) after which it started to decline (B: -0.66 times/month per year; 95% CI -0.92, −0.40). Moreover, both total Hg in hair and fish consumption was positively associated with maternal age and education, and inversely associated with pre-pregnancy BMI. In conclusion, the exposure to MeHg via fish appears to be slowly declining among Swedish pregnant women.