Global fine-scale changes in ambient NO2 during COVID-19 lockdowns.

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1-9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910-20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Sustainable hydrogen production via microalgae: Technological advancements, economic indicators, environmental aspects, challenges, and policy implications.

Hydrogen has emerged as an alternative energy source to meet the increasing global energy demand, depleting fossil fuels and environmental issues resulting from fossil fuel consumption. Microalgae-based biomass is gaining attention as a potential source of hydrogen production due to its green energy carrier properties, high energy content, and carbon-free combustion. This review examines the hydrogen production process from microalgae, including the microalgae cultivation technological process for biomass production, and the three main routes of biomass-to-hydrogen production: thermochemical conversion, photo biological conversion, and electrochemical conversion. The current progress of technological options in the three main routes is presented, with the various strains of microalgae and operating conditions of the processes. Furthermore, the economic and environmental perspectives of biomass-to-hydrogen from microalgae are evaluated, and critical operational parameters are used to assess the feasibility of scaling up biohydrogen production for commercial industrial-scale applications. The key finding is the thermochemical conversion process is the most feasible process for biohydrogen production, compared to the pyrolysis process. In the photobiological and electrochemical process, pure hydrogen can be achieved, but further process development is required to enhance the production yield. In addition, the high production cost is the main challenge in biohydrogen production. The cost of biohydrogen production for direct bio photolysis it cost around $7.24 kg-1; for indirect bio photolysis it costs around $7.54 kg-1 and for fermentation, it costs around $7.61 kg-1. Therefore, comprehensive studies and efforts are required to make biohydrogen production from microalgae applications more economical in the future.

Alterations in Daphnia magna exposed to enniatin B and beauvericin provide additional value as environmental indicators.

Mycotoxins beauvericin (BEA) and enniatin B (ENN B) affect negatively several systems and demand more studies as the mechanisms are still unclear. The simultaneous presence of contaminants in the environment manifests consequences of exposure for both animals and flora. Daphnia magna is considered an ideal invertebrate to detect effects of toxic compounds and environmental alterations. In this study, the potential toxicity and the basic mechanism of BEA and ENN B individually and combined were studied in D. magna. Acute and delayed toxicity were evaluated, and transcript levels of genes involved in xenobiotic metabolism (mox, gst, abcb1, and abcc5), reproduction, and oxidative stress (vtg-SOD) were analyzed by qPCR. Though no acute toxicity was found, results revealed a spinning around and circular profile of swimming, a strong decrease of survival after 72 h for BEA and ENN B at 16 µM and 6.25 µM, respectively, while for BEA + ENN B [8 + 1.6] µM after 96 h. The amount of mycotoxin remaining in the media revealed that the higher the concentration assayed the higher the amount remaining in the media. Differential regulation of genes suggests that xenobiotic metabolism is affected denoting different effects on transcription for tested mycotoxins. The results provide new insights into the underlying risk assessment of BEA and ENN B not only through food for consumers but also for the environment.

Early Season Environmental Indicators of Wheat Stripe Rust Epidemics in Kansas and the Central Great Plains Region of the United States.

During the past two decades, the wheat-producing areas of the Great Plains region in North America experienced frequent, severe yield losses to stripe rust (Puccinia striiformis f. sp. tritici). In general, outbreaks of rust diseases in the Southern Great Plains region often precede disease problems in the Central and Northern Great Plains. However, these generalizations provide little information, and our objective for this study was to identify weather variables, geographical areas, and time periods that influence the early stages of stripe rust epidemics in the Great Plains. Data used in this analysis consisted of monthly summaries of temperature, precipitation, and soil moisture from 10 climate districts in Texas of the United States. These environmental variables were paired with estimates of wheat yield losses to stripe rust in Kansas from 2000 to 2019, with yield loss coded as a binary variable (1 = >4% statewide yield loss). An ensemble of simple models representing weather variables, time periods, and geographical locations were hypothesized to be influential in the development of stripe rust epidemics. Model performance was verified with observations not used in model development. Results of this study indicated that soil moisture within two to three climate districts in Texas were particularly influential in regional disease development. These areas of Texas were 700 to 1,000 km away from locations in Kansas where the disease-related yield losses were observed, and they often preceded disease losses by 3 to 6 months. In the future, these models could help establish priority locations and time periods for disease scouting and inform regional estimates of disease risk.

Application of spatial environmental indicators in the assessment of degradation potential of water resources in water basins.

Changes in land use have been occurring in a continuous and disorderly way in recent decades due to rapid population growth and the growing demand for food. These constant changes result in a series of harmful effects to the environment, especially to water resources, significantly changing their availability and quality. This study aims to evaluate the degradation potential of watersheds through an evaluation of some environmental indicators using arithmetic means to construct an index called in this research "index of potential environmental degradation" (IPED). To form the IPED, the hydrographic sub-basins of the Sorocabuçu River, located in the central west of the State of São Paulo, Brazil, comprised the study area. The results showed that most hydrographic sub-basins, that is, eight units, present degradation values ranging from moderate to very high, resulting mainly from low conservation values of forests plus a use destined to the planting of temporary cultures depending on good physical conditions. On the other hand, only one sub-basin showed a low degradation value. The methodology used for the development of the IPED is easy to apply and an effective tool for environmental analyses. It may contribute to studies and forms of planning and land use management aiming the conservation of water resources and protected areas and reduction of degradation.

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of weather and vegetation conditions: applications for Brazilian biomes.

The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P-ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling showed suitability for monitoring the water and vegetation conditions, making way to detect anomalies for specific periods along the year by using historical images and weather data, with strong potential to support public policies for management and conservation of natural resources and with possibilities for replication of the methods in other countries.

Nurse-sensitive environmental indicators: A qualitative study.

AIM: This study aims to explore the proposed concept of "nurse-sensitive environmental indicators" among nursing and non-nursing leaders of environmental stewardship who work with nurses. BACKGROUND: Aligned with the Sustainable Development Goals, nurses are obligated to "practice in a manner that advances environmental safety and health." Little is known about environmental impacts in acute-care nursing. METHODS: Nursing and non-nursing leaders of environmental stewardship across the United States (N = 9) were interviewed to explore the concept of acute-care nurse-sensitive environmental indicators. Transcripts were examined using qualitative descriptive analysis. RESULTS: Thematic analysis revealed that nurses are in key positions to influence environmental change, need more education and awareness to be effective, and need leadership support and role-modelling. Issues related to waste were highly nurse sensitive; issues related to food, chemicals, and transportation were moderately nurse sensitive; issues related to energy and water were minimally nurse sensitive. CONCLUSION: Preliminary consensus on nurse-sensitive environmental indicators was confirmed by leader participants in this study. IMPLICATIONS FOR NURSING MANAGEMENT: To help meet environmentally focused Sustainable Development Goals, nursing leaders can use the concept of nurse-sensitive environmental indicators in planning, education, resource allocation, and leadership to improve environmental stewardship in acute care nursing.

Leaf reflectance and functional traits as environmental indicators of urban dust deposition.

BACKGROUND: How to quickly predict and evaluate urban dust deposition is the key to the control of urban atmospheric environment. Here, we focus on changes of plant reflectance and plant functional traits due to dust deposition, and develop a prediction model of dust deposition based on these traits. RESULTS: The results showed that (1) The average dust deposition per unit area of Ligustrum quihoui leaves was significantly different among urban environments (street (18.1001 g/m2), community (14.5597 g/m2) and park (9.7661 g/m2)). Among different urban environments, leaf reflectance curves tends to be consistent, but there were significant differences in leaf reflectance values (park (0.052-0.585) > community (0.028-0.477) > street (0.025-0.203)). (2) There were five major reflection peaks and five major absorption valleys. (3) The spectral reflectances before and after dust removal were significantly different (clean leaves > dust-stagnant leaves). 695 ~ 1400 nm was the sensitive range of spectral response. (4) Dust deposition has significant influence on slope and position of red edge. Red edge slope was park > community > street. After dust deposition, the red edge position has obviously "blue shift". The moving distance of the red edge position increases with the increase of dust deposition. The forecast model of dust deposition amount established by simple ratio index (y = 2.517x + 0.381, R2 = 0.787, RMSE (root-mean-square error) = 0.187. In the model, y refers to dust retention, x refers to simple ratio index.) has an average accuracy of 99.98%. (5) With the increase of dust deposition, the specific leaf area and chlorophyll content index decreased gradually. The leaf dry matter content, leaf tissue density and leaf thickness increased gradually. CONCLUSION: In the dust-polluted environment, L. quihoui generally presents a combination of characters with lower specific leaf area, chlorophyll content index, and higher leaf dry matter content, leaf tissue density and leaf thickness. Leaf reflectance spectroscopy and functional traits have been proved to be effective in evaluating the changes of urban dust deposition.

The impact of COVID 19 on air pollution levels and other environmental indicators - A case study of Egypt.

The outbreak of coronavirus disease (COVID-19) not only affected health and economics, but also its effect extended to include other aspects, such as the environment. Using Egypt as a case study, this paper presents the impact of COVID-19 pandemic on air pollution levels by studying nitrogen dioxide (NO2), ozone (O3), particulate matter represented in absorbing aerosol index (AAI), carbon monoxide (CO), and greenhouse gas (GHG) emissions. The paper also highlights the impact of COVID-19 pandemic on other environmental indicators including environmental noise, medical and municipal solid wastes. The paper presents the Egyptian COVID-19 story from its different angles including the development of confirmed COVID-19 cases, containment measures from the government, the impact on the country's economy and the national energy consumption so as to effectively evaluate the effect on both the air pollution levels and the other studied environmental indicators. For the other environmental indicators, a strong link was observed between COVID-19 lockdown and the reduction in environmental noise, beaches, surface and groundwater pollution. For environmental noise, this has been confirmed by officially governmental announcements which reported that the level of environmental noise in Egypt was reduced by about 75% during the lockdown period. On the other hand, there are some negative effects, including an increase in medical solid waste (from 70 to 300 ton/day), municipal solid waste, as well as a less efficient solid waste recycling process. For air pollution levels, the data were obtained from National Aeronautics and Space Administration (NASA) and European Space Agency satellite data sets. The data for the lockdown period in 2020 have been extracted and compared to the corresponding months in the selected baseline period (2015-2019) to identify the effect that the lockdown period had on the air pollution levels in Egypt with focus on Cairo and Alexandria governorates. It was found that the AAI decreased by about 30%, the NO2 decreased by 15 and 33% over Cairo and Alexandria governorates, respectively, and that the CO decreased by about 5% over both governorates. In addition, the GHG emissions in Egypt were reduced by at least 4% during the pandemic. In contrast, ozone levels increased by about 2% over Cairo and Alexandria governorates. It can be concluded that the implemented containment measures during COVID-19 pandemic had resulted in both positive and negative environmental impacts. The positive environmental impacts are not sustainable and deterioration on them is expected to occur after the lockdown as it was before the pandemic. Therefore, stricter laws must be enacted to protect the environment in Egypt.

Control of Salvinia molesta with imazamox and analysis of environmental indicators in microcosms.

The aim of this study was to assess the efficacy of imazamox for control of S. molesta and to assess the effects of plant decomposition on environmental indicators after application of this herbicide in microcosm conditions. The following rates were used: 600, 700, 800 and 900 g ai ha-1 and spray volume 50 L ha-1. Control efficacy was determined as the percentage (from 0 to 100%) of visible injury symptoms in the plants, biochemical and chemical oxygen demand (BOD5 and COD), water quality variables, chlorophyll a and pheophytin a at 0, 7, 15, 30, 45 and 60 days after application (DAA) and fresh and dry biomass at 60 DAA. Imazamox was effective in controlling 94% of S. molesta with 900 g ai ha-1; it reduced 95% of fresh weight and 92% of dry weight of plant at 60 DAA, and reduced chlorophyll a of the plants for all rates. For BOD5, there was an increase for all rates at 15, 30 and 45 DAA with restoration of the parameters at 60 DAA, and for COD, there was an increase at 60 DAA with 700 and 900 g ai ha-1. For temperature, pH, dissolved oxygen and electrical conductivity, there was no significant effect after spraying. Imazamox was effective in controlling S. molesta with 900 g ai ha-1 without causing significant effects on the physical-chemical parameters of water quality.

Electrostatic spraying of imazamox to control the floating aquatic plant Salvinia molesta and its effects on environmental indicators of water quality.

This study aimed to assess, in a microcosm condition, the efficacy of electrostatic spraying of herbicide imazamox in the control of Salvinia molesta and the effects of decomposition of plant material on water quality. The herbicide rates used were 600, 700, 800, and 900 g ai ha-1 and spray volume of 50 L ha-1 in electrostatic application. Control effectiveness was assessed at 7, 15, 30, 45, and 60 days after application (DAA), expressed in percentage (0-100%) of visible injury symptoms in the plants, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), chlorophyll a and pheophytin a contents at 0, 7, 15, 30, 45, and 60 DAA, and fresh and dry biomass at 60 DAA. Imazamox was effective in controlling 63% of S. molesta with 900 g ai ha-1 in 45 DAA and 30% with 800 g ai ha-1 in 30 DAA, and reduced 82.3% and 17.5% of fresh weight and 62.6% and 9.3% of dry weight of plant at 60 DAA, respectively. The imazamox spray reduced chlorophyll a with all doses applied and increased BOD5 in 45 DAA with 900 g ai ha-1 and COD in all assessment periods, but for temperature, dissolved oxygen, electrical conductivity, and pH, there was no significant effect after spraying. The herbicide imazamox reduced S. molesta plants with 900 g ai ha-1, without causing significant effects on environmental indicators of water quality. Electrostatic spraying of herbicide can be used in management strategies of aquatic plants to reduce plant density in water bodies and maintain the colonization of plants at a level not harmful to the aquatic biota.

The influence of the correlation-covariance structure of measurement errors over uncertainties propagation in online monitoring: application to environmental indicators in SUDS.

This paper presents a methodology to assess the influence of the correlation-covariance structure of measurement errors in online monitoring over the propagation of uncertainties, applied to wet-weather environmental indicators in sustainable urban drainage systems (SUDSs). The effect of auto-correlated and heteroskedastic errors in measured time-series over the estimated probability density function (PDF) of different environmental indicators is analyzed for a wide variety of possible error structures in the data. For this purpose, multiple correlation-covariance structures are randomly generated from exploring the parametric space of a linear exponent autoregressive (LEAR) model, employing a Bayesian-based Markov Chain Monte Carlo sampling technique. Significant differences tests are proposed to identify the most correlated parameters of the correlation-covariance error model with statistics of the environmental indicator PDFs. The method is applied to total suspended solids (TSS) and chemical oxygen demand (COD) time-series recorded during 13 rainfall events at the inlet and outlet of a SUDS train (stormwater settling tank-horizontal constructed wetland). In this case, results showed that the total error in the estimation of the analyzed environmental indicators is mostly explained by standard uncertainties (flattening of the PDFs) rather than bias contributions (displacement of the PDFs). The correlation-covariance model parameters related to the temporal delimitation of hydrographs/pollutographs and the intensity of the autocorrelation showed to have the strongest influence in the propagation of measurement errors (flattening/displacement of the PDFs).

Temporal variability of environmental indicators for agriculture in Albania.

This study aimed to reveal the trends in soil nutrient (NPK) balances for agricultural land in Albania for the period 1950-2019, through the analysis of the main NPK sources to NPK inputs and outputs. The results showed a large temporal variation in the balances of these nutrients, especially nitrogen. This variability depends mainly on the dynamics of land use change, the amount of chemical fertilizers used, and the number of animals during study period. For all three soil nutrients, negative trends have been observed in their balance sheets. From 1950 to 1990, the negative balance has declined, returning to positive for nitrogen in 1990 and phosphorus between 1970 and 2000, but has increased again in the last two to three decades. For 2019, the deficit for N was -104.8 kg ha1, for P -8.7 kg ha-1, and for K -134.5 kg ha-1, making Albania have the largest deficit of soil nutrients compared to EU and OECD countries. This deficit is mainly due to the application of small amounts of chemical fertilizers. In this context, the increase in crop yields in the last two decades seems to be related more to the improvement of plant production technologies than to the increase in the use of nitrogen and potassium fertilizers. Currently, there appears to be no environmental pressure or potential risk of pollution at nationwide scale. However, this risk may exist at regional and field scales. Therefore, the assessment of soil nutrient balance at these two scales is necessary.

Annual rhythms of milk synthesis in dairy herds in 4 regions of the United States and their relationships to environmental indicators.

The annual rhythms of milk and milk component yields are not well described and are important to dairy management. Recent analysis of federal milk marketing orders in the United States observed that the amplitude and time at peak (acrophase) of the rhythms of milk fat and protein concentration differ among regions, but the rhythms of milk and milk component yields are not well described. Our objective was to determine the annual rhythms of milk and milk component production from 4 US regions at the herd level and examine potential environmental factors entraining these rhythms. Monthly Dairy Herd Improvement Association records of all available herds in Pennsylvania (PA), Minnesota (MN), Texas (TX), and Florida (FL) from the years 2003 to 2016 were obtained from Dairy Records Managements Systems. Milk yield, fat and protein yield, and fat and protein concentration were fit to the linear form of the cosine function with a 12-mo period using a linear mixed effects model. Additionally, the fit of models containing either the cosine function or environmental temperature were compared using an F-test. Milk yield and fat and protein yields and concentrations fit a cosine function in all 4 states, indicating an annual rhythm. The amplitude (peak to mean) of the rhythm of milk yield varied by state and was lower in PA (1.2 kg) and MN (1.2 kg) compared with TX (3.1 kg) and FL (3.3 kg). Fat and protein yields similarly showed greater amplitudes in the southern versus northern states. The amplitudes of the rhythms of fat and protein concentration were opposite by region, with greater amplitudes occurring in MN and PA than in TX and FL. The acrophases of milk yield and milk fat and protein yields and concentrations also varied by state, but all peaked between October and March. An annual rhythm fit the data better than changes in environmental temperature for all responses in all states, except for fat and protein concentrations in FL, which exhibited lower amplitude seasonal rhythms. The yearly pattern of milk yield closely followed the fixed yearly pattern of the day to day changes in day length, whereas the rhythms of milk fat and protein concentrations followed the yearly pattern of absolute day length. Results suggest that the region of the United States in which a herd is located affects their annual rhythms of production, with a greater yearly variation in milk, fat, and protein yields occurring in the southern United States. The consistency of annual rhythms across years and herds allowed development of regression equations to adjust expectations across the year to account for the annual rhythm.

Sucralose and acesulfame as an indicator of domestic wastewater contamination in Wuhan surface water.

Artificial sweeteners (ASs) are applied widely as sucrose substitutes in food, pharmaceuticals, and personal-care products, which results in their release into surface water. The occurrence of ASs in aquatic environments in China has rarely been reported. In this study, we determined the concentration of seven ASs in surface water and sediment samples from 16 lakes in Wuhan. The sum of the ASs concentration ranged from 0.89 to 20.6 µg/L in the surface water, with a mean value of 4.96 ± 5.16 µg/L. The most abundant AS was sucralose (SUC), with a concentration from 0.33 to 18.0 µg/L, followed by acesulfame (ACE) (0.40-2.78 µg/L), saccharin (SAC) (

Risk management, signal processing and econometrics: A new tool for forecasting the risk of disease outbreaks.

This paper takes a novel approach for forecasting the risk of disease emergence by combining risk management, signal processing and econometrics to develop a new forecasting approach. We propose quantifying risk using the Value at Risk criterion and then propose a two staged model based on Multivariate Singular Spectrum Analysis and Quantile Regression (MSSA-QR model). The proposed risk measure (PLVaR) and forecasting model (MSSA-QR) is used to forecast the worst cases of waterborne disease outbreaks in 22 European and North American countries based on socio-economic and environmental indicators. The results show that the proposed method perfectly forecasts the worst case scenario for less common waterborne diseases whilst the forecasting of more common diseases requires more socio-economic and environmental indicators.

Analysis of tail coiling activity of zebrafish (Danio rerio) embryos allows for the differentiation of neurotoxicants with different modes of action.

In (eco)toxicology, there is a critical need for efficient methods to evaluate the neurotoxic potential of environmental chemicals. Recent studies proposed analysis of early coiling activity in zebrafish embryos as a powerful tool for the identification of neurotoxic compounds. In order to demonstrate that the analysis of early tail movements of zebrafish embryos allows for the discrimination of neurotoxicants acting via different mechanisms, the present study investigated the effects of four different neurotoxicants on the embryogenesis (fish embryo toxicity test) and early tail coiling movements of zebrafish embryos. Cadmium predominantly increased the frequency of tail coiling at the late pharyngula stage. Dichlorvos delayed embryonic development and caused convulsive tail movements resulting in prolonged duration of tail coils. Embryos exposed to teratogenic concentrations of fluoxetine and citalopram displayed absence of spontaneous tail movements at 24 h post-fertilization. In contrast, a non-teratogenic test concentration of citalopram decreased coiling frequency at multiple time points. Results demonstrated that the analysis of tail coiling movements of zebrafish embryos has the potential to discriminate neurotoxic compounds with different primary modes of action. In addition, chemical-induced effects on coiling activity were shown to potentially overlap with effects on embryogenesis. Further studies are needed to clarify the interplay of unspecific developmental toxicity of neurotoxic chemicals and effects resulting from specific neurotoxic mechanisms.

A Proposal: Nurse-Sensitive Environmental Indicators.

Healthcare contributes significant pollution to the natural environment. Nurses are obligated by professional commitment, to avoid causing harm in their care processes and decisions, including environmental harm. Nurse awareness of healthcare-generated pollution is growing but nurses may lack an understanding of how nursing contributes specifically to this pollution and what nurses can do within their scope and span to address it. This chapter introduces the concept "Nurse-Sensitive Environmental Indicators" as a proposal to identify, measure, and reduce the unintended harm of nursing practice that contributes to healthcare-generated pollution. It discusses the environmental problem, environmental health, and healthcare. The chapter explains what environmental stewardship has to do with nursing and describes nurse sensitive indicators. As has been the case with other quality outcomes measures, identifying agreed-upon environmental outcomes measures may give the nursing profession tools to measure and then address environmental impacts arising from nursing practice.