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In anticipation of growing wildfire management challenges, the Canadian government is investing in WildFireSat, an Earth observation satellite mission designed to collect data in support of Canadian wildfire management. Although costs of the mission can be reasonably estimated, the benefits of such an investment are unknown. Here we forecast the possible benefits of WildFireSat via an avoided cost approach. We consider five socio-economic components: suppression costs (fixed and variable), timber losses, property, asset and infrastructure losses, evacuation costs, and smoke related health costs. Using a Monte Carlo analysis, we evaluated a range of possible changes to these components based on expert opinions. The resulting Net Present Value (NPV) estimates depend on the presumed impact of using WildFireSat decision support data products, with pessimistic and conservative assumptions generating mission costs that typically exceed potential benefits by 1.16 to 1.59 times, while more optimistic assumptions generate benefits in excess of costs by 8.72 to 10.48 times. The analysis here excludes some possibly significant market and non-market impacts expected from WildFireSat due to data limitations; accounting for these additional impacts would likely generate positive NPVs under even cautious impact assumptions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Hope et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water., Competing Interests: The authors have declared that no competing interests exist.

Invasive species can lead to community-level damage to the invaded ecosystem and extinction of native species. Most surveillance systems for the detection of invasive species are developed based on expert assessment, inherently coming with a level of uncertainty. In this research, info-gap decision theory (IGDT) is applied to model and manage such uncertainty. Surveillance of the Asian House Gecko, Hemidactylus frenatus Duméril and Bibron, 1836 on Barrow Island, is used as a case study. Our research provides a novel method for applying IGDT to determine the population threshold ([Formula: see text]) so that the decision can be robust to the deep uncertainty present in model parameters. We further robust-optimize surveillance costs rather than minimize surveillance costs. We demonstrate that increasing the population threshold for detection increases both robustness to the errors in the model parameter estimates, and opportuneness to lower surveillance costs than the accepted maximum budget. This paper provides guidance for decision makers to balance robustness and required surveillance expenditure. IGDT offers a novel method to model and manage the uncertainty prevalent in biodiversity conservation practices and modelling. The method outlined here can be used to design robust surveillance systems for invasive species in a wider context, and to better tackle uncertainty in protection of biodiversity and native species in a cost-effective manner., (© 2021. The Author(s).)

Extreme air quality episodes represent a major threat to human health worldwide but are highly dynamic and exceedingly challenging to monitor. The 2018 Kīlauea Lower East Rift Zone eruption (May to August 2018) blanketed much of Hawai'i Island in "vog" (volcanic smog), a mixture of primary volcanic sulfur dioxide (SO 2 ) gas and secondary particulate matter (PM). This episode was captured by several monitoring platforms, including a low-cost sensor (LCS) network consisting of 30 nodes designed and deployed specifically to monitor PM and SO 2 during the event. Downwind of the eruption, network stations measured peak hourly PM 2.5 and SO 2 concentrations that exceeded 75 μg m -3 and 1,200 parts per billion (ppb), respectively. The LCS network's high spatial density enabled highly granular estimates of human exposure to both pollutants during the eruption, which was not possible using preexisting air quality measurements. Because of overlaps in population distribution and plume dynamics, a much larger proportion of the island's population was exposed to elevated levels of fine PM than to SO 2 Additionally, the spatially distributed network was able to resolve the volcanic plume's chemical evolution downwind of the eruption. Measurements find a mean SO 2 conversion time of ∼36 h, demonstrating the ability of distributed LCS networks to observe reaction kinetics and quantify chemical transformations of air pollutants in a real-world setting. This work also highlights the utility of LCS networks for emergency response during extreme episodes to complement existing air quality monitoring approaches., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Though highly motivated to slow the climate crisis, governments may struggle to impose costly polices on entrenched interest groups, resulting in a greater need for negative emissions. Here, we model wartime-like crash deployment of direct air capture (DAC) as a policy response to the climate crisis, calculating funding, net CO 2 removal, and climate impacts. An emergency DAC program, with investment of 1.2-1.9% of global GDP annually, removes 2.2-2.3 GtCO 2 yr -1 in 2050, 13-20 GtCO 2 yr -1 in 2075, and 570-840 GtCO 2 cumulatively over 2025-2100. Compared to a future in which policy efforts to control emissions follow current trends (SSP2-4.5), DAC substantially hastens the onset of net-zero CO 2 emissions (to 2085-2095) and peak warming (to 2090-2095); yet warming still reaches 2.4-2.5 °C in 2100. Such massive CO 2 removals hinge on near-term investment to boost the future capacity for upscaling. DAC is most cost-effective when using electricity sources already available today: hydropower and natural gas with renewables; fully renewable systems are more expensive because their low load factors do not allow efficient amortization of capital-intensive DAC plants.

Sunscreen is released into the marine environment and is considered toxic for marine life. The current analytical methods for the quantification of sunscreen are mostly specific to individual chemical ingredients and based on complex analytical and instrumental techniques. A simple, selective, rapid, reproducible and low-cost spectrophotometric procedure for the quantification of commercial sunscreen in seawater is described here. The method is based on the inherent properties of these cosmetics to absorb in the wavelength of 300-400 nm. The absorption at 303 nm wavelength correlates with the concentration of most commercial sunscreens. This method allows the determination of sunscreens in the range of 2.5-1500 mg L-1, it requires no sample pretreatment and offers a precision of up to 0.2%. The spectrophotometric method was applied to quantify sunscreen concentrations at an Atlantic Beach with values ranging from 10 to 96.7 mg L-1 in the unfiltered fraction and from the undetectable value to 75.7 mg L-1 in the dissolved fraction. This method is suggested as a tool for sunscreen quantifications in environmental investigations and monitoring programs., Competing Interests: No authors have competing interests.

Point-of-care risk assessment (PCRA) for airborne viruses requires a system that can enrich low-concentration airborne viruses dispersed in field environments into a small volume of liquid. In this study, airborne virus particles were collected to a degree above the limit of detection (LOD) for a real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). This study employed an electrostatic air sampler to capture aerosolized test viruses (human coronavirus 229E (HCoV-229E), influenza A virus subtype H1N1 (A/H1N1), and influenza A virus subtype H3N2 (A/H3N2)) in a continuously flowing liquid (aerosol-to-hydrosol (ATH) enrichment) and a concanavalin A (ConA)-coated magnetic particles (CMPs)-installed fluidic channel for simultaneous hydrosol-to-hydrosol (HTH) enrichment. The air sampler's ATH enrichment capacity (EC) was evaluated using the aerosol counting method. In contrast, the HTH EC for the ATH-collected sample was evaluated using transmission-electron-microscopy (TEM)-based image analysis and real-time qRT-PCR assay. For example, the ATH EC for HCoV-229E was up to 67,000, resulting in a viral concentration of 0.08 PFU/mL (in a liquid sample) for a viral epidemic scenario of 1.2 PFU/m 3 (in air). The real-time qRT-PCR assay result for this liquid sample was "non-detectable" however, subsequent HTH enrichment for 10 min caused the "non-detectable" sample to become "detectable" (cycle threshold (CT) value of 33.8 ± 0.06)., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Oceans and their resources are experiencing immense pressure because of human exploitation. The intensive use of sea areas has become an important method in solving the contradiction between ocean supply and demand, thereby ensuring sustainable marine economy development, tapping potential sea-area utilization, reasonably allocating sea-area utilization structures, and increasing marine economic benefits. This paper explores the definition and connotation of intensive sea-area use and constructs an evaluation index system based on marine input intensity, marine utilization structure, marine economic benefit, and marine ecological environment. Multi-objective variable fuzzy set theory and fuzzy decision analysis methods were used to evaluate the intensive sea-area utilization in the Liaoning Coastal Economic Zone of China during 2004-2016. The spatial differentiation characteristics of intensive sea-area use were analysed using cluster analysis. The research result showed that: (1) Intensive utilization level of the Liaoning coastal economic zone has gradually increased, while it is still in a moderately weak level; (2) Sea area intensive utilization varied in degrees and fluctuates in the six cities under the jurisdiction of the Liaoning coastal economic zone; and (3) Marine input intensity, marine utilization structure, marine economic benefit, and marine sustainability indexes have increased in the cities, thereby exhibiting improvements in the Liaoning coastal economic zone., Competing Interests: The authors have declared that no competing interests exist.

Studying the driving factors of environmental pollution is of great importance for China. Previous literature mainly focused on the cause of national aggregate emission changes. However, research about the effect of fiscal expenditures on science and technology (FESTs) on environmental pollution is rare. Considering the large gap among cities in China, it is necessary to investigate whether and how FESTs affect environmental pollution among cities. We adopted three kinds of typical environmental pollutants including sulfur dioxide (SO 2 ) emissions, wastewater emission, and atmospheric particulate matter less than 2.5 micrometers in diameter (PM 2.5 ). Using the data of 260 prefecture-level cities over ten years in China, we found that FESTs play a significantly positive role in reducing sulfur dioxide (SO 2 ) emissions and PM 2.5 concentrations, but fail to alleviate wastewater emissions. Specifically, for every 1% increase in FESTs, SO 2 emissions were reduced by 5.317% and PM 2.5 concentrations were reduced by 5.329%. Furthermore, we found that FESTs reduced environmental pollution by impeding fixed asset investments and by promoting research and development activities (R&D). Moreover, the impacts of FESTs on environmental pollution varied across regions and sub-periods. Our results are robust to a series of additional checks, including alternative econometric specifications, generalized method of moments (GMM) analysis and overcoming potential endogeneity with an instrumental variable. Our findings confirm that government efforts can be effective on pollution control in China. Hence, all governments should pay more attention to FESTs for sustainable development and environmental quality improvements., Competing Interests: The authors declare no conflict of interest.

(1) Background: Small, lightweight, low-cost optical particulate matter (PM) monitors are becoming popular in the field of occupational exposure monitoring, because these devices allow for real-time static measurements to be collected at multiple locations throughout a work site as well as being used as wearables providing personal exposure estimates. Prior to deployment, devices should be evaluated to optimize and quantify measurement accuracy. However, this can turn out to be difficult, as no standardized methods are yet available and different deployments may require different evaluation procedures. To gain insight in the relevance of different variables that may affect the monitor readings, six PM monitors were selected based on current availability and evaluated in the laboratory; (2) Methods: Existing strategies that were judged appropriate for the evaluation of PM monitors were reviewed and seven evaluation variables were selected, namely the type of dust, within- and between-device variations, nature of the power supply, temperature, relative humidity, and exposure pattern (peak and constant). Each variable was tested and analyzed individually and, if found to affect the readings significantly, included in a final correction model specific to each monitor. Finally, the accuracy for each monitor after correction was calculated; (3) Results: The reference materials and exposure patterns were found to be main factors needing correction for most monitors. One PM monitor was found to be sufficiently accurate at concentrations up to 2000 µg/m 3 PM 2.5 , with other monitors appropriate at lower concentrations. The average accuracy increased by up to three-fold compared to when the correction model did not include evaluation variables; (4) Conclusions: Laboratory evaluation and readings correction can greatly increase the accuracy of PM monitors and set boundaries for appropriate use. However, this requires identifying the relevant evaluation variables, which are heavily reliant on how the monitors are used in the workplace. This, together with the lack of current consensus on standardized procedures, shows the need for harmonized PM monitor evaluation methods for occupational exposure monitoring.

Environmental contamination affects human health and reduces the quality of life. Therefore, the monitoring of water and air quality is important, ensuring that all areas are acquiescent with the current legislation. Colorimetric sensors deliver quick, naked-eye detection, low-cost, and adequate determination of environmental analytes. In particular, disposable sensors are cheap and easy-to-use devices for single-shot measurements. Due to increasing requests for in situ analysis or resource-limited zones, disposable sensors' development has increased. This review provides a brief insight into low-cost and disposable colorimetric sensors currently used for environmental analysis. The advantages and disadvantages of different colorimetric devices for environmental analysis are discussed.

Tectonic lakes are among the most geologically fascinating and environmentally versatile hydrobiological systems found on the earth's surface. We conducted a study on the limnology of Tasek Lake, a tectonic lake located in the Indo-Burma Province of the South Asian region. Physico-chemical parameters of the lake's water along with its plankton were considered for the study. Their relationship was analysed by understanding their seasonal variations and through linear regression models. The water quality index (WQI), plankton diversity indices and canonical correspondence analysis (CCA) were computed. The ichthyofaunal diversity was also studied to get an insight into the lake's fishery potential. A preliminary assessment on the economic feasibility of converting Tasek Lake into a fishery was also completed. Results indicate moderate eutrophication in the lake and the plankton population is observed to be rich and abundant. The WQI value confirms the water to be of "very poor" quality. The CCA was done to analyze the relationships of physico-chemical parameters with months and seasons, and the relation between seasons and plankton assemblages. Results corroborate the results of WQI. Identified fish population suggest ample fishery potential of the lake. The economic assessment reveals that in order to maintain the ecological sustainability of the lake, it should be transformed into a recreational fishery, following a catch-and-release model. The study calls for urgent restoration of the lake so that not only its pristine ecology is survived but also its fishery potential is sustainably harnessed and local livelihood is improved., Competing Interests: The authors have declared that no competing interests exist.

Ambient air pollution in urban cities in sub-Saharan Africa (SSA) is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM 2.5 ). On most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM 2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24 h concentration measured across all sites was 38 µg/m 3 with the highest PM 2.5 period average concentration of 91 µg/m 3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m 3 measured in Faraja, The Gambia. Kampala in Uganda and Nnewi in Nigeria recorded the longest periods with concentrations >250µg/m 3 . Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM 2.5 concentrations in SSA countries. Such data are crucially needed to raise public, societal and policymaker awareness about air pollution across SSA., Competing Interests: The authors declare no conflict of interest.

Microplastics are ubiquitous in our environment and are found in rivers, streams, oceans, and even tap water. Riverine microplastics are relatively understudied compared with those in marine ecosystems. In Oregon (USA), we sampled 8 sites along 4 freshwater rivers spanning rural to urban areas to quantify microplastics. Plankton tow samples from sites along the Columbia, Willamette, Deschutes, and Rogue Rivers were analyzed using traditional light microscopy for initial microplastic counts. Application of Nile Red dye to validate microplastics improved microplastic identification, particularly for particles (Wilcox test; p = 0.001). Nile Red-corrected microfiber abundance was correlated with human population within 5 km of the sample site (R² = 0.554), although no such relationship was observed between microparticles and population (R² = 0.183). We found that plastics were present in all samples from all sites, despite the range from undeveloped, remote stretches of river in rural areas to metropolitan sites within Portland (OR, USA), demonstrating the pervasive presence of plastic pollution in freshwater ecosystems. Environ Toxicol Chem 2020;39:1590-1598. © 2020 SETAC., (© 2020 SETAC.)

Excess evaporation within the Persian (also referred as the Arabian) Gulf induces an inverse-estuary circulation. Surface waters are imported, via the Strait of Hormuz, while saltier waters are exported in the deeper layers. Using output of a 1/12-Degree horizontal resolution ocean general circulation model, the spatial structure and time variability of the circulation and the exchanges of volume and salt through the Strait of Hormuz are investigated in detail. The model's circulation pattern in the Gulf is found to be in good agreement with observations and other studies based on numerical models. The mean export of salty waters in the bottom layer is of 0.26±0.05Sv (Sverdrup = 1.0 × 106 m3 s-1). The net freshwater import, the equivalent of the salt export divided by a reference salinity, done by the baroclinic circulation across that vertical section is decomposed in an overturning and a horizontal components, with mean values of 7.2±2.1 × 10-3 Sv and 5.0±1.7 × 10-3 Sv respectively. An important, novel finding of this work is that the horizontal component is confined to the deeper layers, mainly in the winter. It is also described for the first time that both components are correlated at the same level with the basin averaged evaporation minus precipitation (E-P) over the Persian Gulf. The highest correlation (r2 = 0.59) of the total freshwater transport across 26°N with E-P over the Gulf is found with a one-month time lag, with E-P leading. The time series of freshwater import does not show any significant trend in the period from 1980 to 2015. Power spectra analysis shows that most of the energy is concentrated in the seasonal cycle. Some intraseasonal variability, likely related to the Shamal wind phenomenon, and possible impacts of El-Nino are also detected. These results suggest that the overturning and the horizontal components of freshwater exchange across the Strait of Hormuz are both driven by dynamic and thermodynamic processes inside the Persian Gulf., Competing Interests: The authors have declared that no competing interests exist.

Noise pollution reduction in the environment is a major challenge from a societal and health point of view. To implement strategies to improve sound environments, experts need information on existing noise. The first source of information is based on the elaboration of noise maps using software, but with limitations on the realism of the maps obtained, due to numerous calculation assumptions. The second is based on the use of measured data, in particular through professional measurement observatories, but in limited numbers for practical and financial reasons. More recently, numerous technical developments, such as the miniaturization of electronic components, the accessibility of low-cost computing processors and the improved performance of electric batteries, have opened up new prospects for the deployment of low-cost sensor networks for the assessment of sound environments. Over the past fifteen years, the literature has presented numerous experiments in this field, ranging from proof of concept to operational implementation. The purpose of this article is firstly to review the literature, and secondly, to identify the expected technical characteristics of the sensors to address the problem of noise pollution assessment. Lastly, the article will also put forward the challenges that are needed to respond to a massive deployment of low-cost noise sensors.

Low-cost airborne particle sensors are gaining attention for monitoring human exposure to indoor particulate matter. This study aimed to establish the concentrations at which these commercially available sensors can be expected to report accurate concentrations. We exposed five types of commercial integrated devices and three types of "bare" low-cost particle sensors to a range of concentrations generated by three different sources. We propose definitions of upper and lower bounds of functional range based on the relationship between a given sensor's output and that of a reference instrument during a laboratory experiment. Experiments show that the lower bound can range from approximately 3 to 15 μg/m 3 . At greater concentrations, sensor output deviates from linearity at approximately 300-3000 μg/m 3 . We also conducted a simulation campaign to analyze the effect of this limitation on functional range on the accuracy of exposure readings given by these devices. We estimate that the upper bound results in minimal inaccuracy in exposure quantification, and the lower bound can result in as much as a 50% error in approximately 10% of US homes., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Integration of low-cost air quality sensors with the internet of things (IoT) has become a feasible approach towards the development of smart cities. Several studies have assessed the performance of low-cost air quality sensors by comparing their measurements with reference instruments. We examined the performance of a low-cost IoT particulate matter (PM 10 and PM 2.5 ) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM 10 -PM 2.5 sensor (SDS011), a temperature and relative humidity sensor (BME280) and an IoT board (ESP8266/Node MCU). Field tests were conducted at three regulatory monitoring stations during the 2018 austral winter and spring seasons. The sensors at each site were operated in parallel with continuous reference air quality monitors (BAM 1020 and TEOM 1400) and a filter-based sampler (Partisol 2000i). Variability between sensor units (n = 7) and the correlation between the sensor and reference instruments were examined. Moderate inter-unit variability was observed between sensors for PM 2.5 (normalized root-mean-square error 9-24%) and PM 10 (10-37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM 2.5 (R 2 0.47-0.86) than PM 10 (0.24-0.56). The correlations (R 2 ) between the 24-h PM 2.5 averages from the sensors and reference instruments were 0.63-0.87 for continuous monitoring and 0.69-0.93 for filter-based samplers. Correlation analysis revealed that sensors tended to overestimate PM concentrations in high relative humidity (RH > 75%) and underestimate when RH was below 50%. Overall, the prototype evaluated exhibited adequate performance and may be potentially suitable for monitoring daily PM 2.5 averages after correcting for RH.

An extensive evaluation of low-cost dust sensors was performed using an exponentially decaying particle concentration. A total of 264 sensors including 27 sensors with light-emitting diodes (LEDs) and 237 sensors with laser lighting sources were tested. Those tested sensors were classified into 4 groups based on the deviation from the reference data obtained by a reference instrument. The response linearities of all the tested samples for PM 1 , PM 2.5 , and PM 10 were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM 1 and PM 2.5 , the lighting source, that is, LED or laser, did not show any significant difference in overall sensor performance. However, LED-based sensors did not perform well for PM 10 measurements. The 32, 24, and 16% of all the tested sensors for PM 1 , PM 2.5 , and PM 10 measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM 10 measurement was relatively less satisfactory., (© 2019 The Authors. Indoor Air published by John Wiley & Sons Ltd.)

Regulatory monitoring networks are often too sparse to support community-scale PM 2.5 exposure assessment while emerging low-cost sensors have the potential to fill in the gaps. To date, limited studies, if any, have been conducted to utilize low-cost sensor measurements to improve PM 2.5 prediction with high spatiotemporal resolutions based on statistical models. Imperial County in California is an exemplary region with sparse Air Quality System (AQS) monitors and a community-operated low-cost network entitled Identifying Violations Affecting Neighborhoods (IVAN). This study aims to evaluate the contribution of IVAN measurements to the quality of PM 2.5 prediction. We adopted the Random Forest algorithm to estimate daily PM 2.5 concentrations at a 1-km spatial resolution using three different PM 2.5 datasets (AQS-only, IVAN-only, and AQS/IVAN combined). The results show that the integration of low-cost sensor measurements is an effective way to significantly improve the quality of PM 2.5 prediction with an increase of cross-validation (CV) R 2 by ~0.2. The IVAN measurements also contributed to the increased importance of emission source-related covariates and more reasonable spatial patterns of PM 2.5 . The remaining uncertainty in the calibrated IVAN measurements could still cause apparent outliers in the prediction model, highlighting the need for more effective calibration or integration methods to relieve its negative impact., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The chemical composition of air changes from moment to moment. While the atmosphere may appear clear and cloudless to the human eye, gases, aerosols, and particulates are in constant interaction with Earth's surface under the influence of meteorological conditions. The recent emergence of low-cost, dense environmental air quality monitoring networks suggests growing interest in highly granular temporospatial exposure assessments by scientists and citizens. This chapter describes the utility of leveraging partnerships and resources to collocate a dense network of low-cost air quality sensors with meteorological sensors across a predominantly rural state located in the southeastern U.S. Construction of the network will improve knowledge on the daily, diurnal, and seasonal variations of pollutant exposures in rural and urban areas, the public health impact of extreme climatological and atmospheric events, and socioeconomic factors that heighten risk of exposures and health outcomes., (© Copyright 2020 Springer Publishing Company, LLC.)

The reliable quantification of perfluoroalkyl carboxylic acids (PFCAs) in environmental samples like surface water by using gas chromatography (GC) remains challenging because the polar PFCAs call for derivatization before injection and problems involving the integration of sample pretreatment and derivatization procedures. Here we proposed a cost-effective method for the GC based determination of C4-C12 PFCAs in surface water samples by integrating solid phase extraction and PFCAs anilide derivatization. First, we assessed the performance of different PFCAs derivatization methods, namely esterification and amidation. Esterification was unable to derivatize C4-C6 PFCAs. On the contrary, amidation procedures by using 2,4-difluoroaniline (DFA) and N , N '-dicyclohexylcarbodiimide (DCC) could successfully transform all the PFCA analogs to produce anilide derivatives, which could be easily detected by GC. Then the reaction conditions in the amidation approach were further optimized by using orthogonal design experiments. After optimizing the instrumental parameters of GC, the limits of detection (LOD) of this derivatization method were determined to be 1.14-6.32 μg L -1 . Finally, in order to establish an intact method for the quantification of PFCAs in surface water samples, solid phase extraction (SPE) was used for extraction and cleanup, which was further integrated with the subsequent amidation process. The SPE-amidation-GC method was validated for application, with good accuracy and precision reflected by the PFCAs recoveries and derivatization of triplicates. The method reported here could provide a promising and cost-effective alternative for the simultaneous determination of C4-C12 PFCAs in environmental water samples.

Often, beach litter monitoring strategies focus only on macro-litter (>25 mm) and do not distinguish between litter left at beaches and litter washed up onshore. We tested inexpensive and user-friendly methods to examine meso-litter (5-25 mm) and large micro-litter (2-5 mm) washed up on German sandy beaches and evaluated our methods regarding the requirements of the Marine Strategy Framework Directive. With a sieve accumulation zone monitoring method, tested 41 times, we found 0.2-21.2 litter pieces/m 2 (⌀ 5.3 pieces/m 2  ± 8.9). With a bare eye accumulation zone monitoring method, tested 10 times, at other beaches, 9.1-65.6 litter pieces/m 2 (⌀ 31.8 pieces/m 2  ± 15.7) were found. Both methods are inexpensive, useful for volunteers, and can be carried out quickly, but are also limited, as they cannot be used regularly. A tested webcam and a modified Braun-Blanquet method turned out to be less suitable., (Copyright © 2019. Published by Elsevier Ltd.)

Background: Occupational heat exposure is a serious concern for worker health, productivity, and the economy. Few studies in North America assess how on-site wet bulb globe temperature (WBGT) levels and guidelines are applied in practice., Methods: We assessed the use of a WBGT sensor for localized summertime heat exposures experienced by outdoor laborers at an industrial worksite in Ontario, Canada during the warm season (May-October) from 2012 to 2018 inclusive. We further examined informed decision making, approximated workers' predicted heat strain (sweat loss, core temperature), and estimated potential financial loss (via hourly wages) due to decreased work allowance in the heat., Results: Significantly higher worksite WBGT levels occured compared with regional levels estimated at the airport, with an upward trend in heat warnings over the 7 years and expansion of warnings into the fall season. The maximum WBGT during warnings related strongly to predicted hourly sweat loss. On average, 22 hours per worker were lost each summer (~1% of annual work hours) as a result of taking breaks or stopping due to heat. This amount of time corresponded to an average individual loss of C$1100 Canadian dollars (~C$220,000 combined for ~200 workers) to workers or the company. The additional losses for an enterprise due to reduced product output were not estimated., Conclusions: Worksite observations and actions at the microscale are essential for improving the estimates of health and economic costs of extreme heat to enterprises and society. Providing worksite heat metrics to the employees aids in appropriate decision making and health protection., (© 2019 Wiley Periodicals, Inc.)

Background: Particle air pollution has adverse health effects, and low-cost monitoring among a large population group is an effective method for performing environmental health studies. However, concern about the accuracy of low-cost monitors has affected their popularization in monitoring projects., Objective: To calibrate a low-cost particle monitor (HK-B3, Hike, China) through a controlled exposure experiment., Methods: Our study used a MicroPEM monitor (RTI, America) as a standard particle concentration measurement device to calibrate the Hike monitors. A machine learning model was established to calibrate the particle concentration obtained by the low-cost PM 2.5 monitors, and ten-fold validation was used to test the model. In addition, we used a linear regression model to compare the results of the machine learning model. A calibration method was established for the low-cost monitors, and it can be used to apply the monitors in future air pollution monitoring projects., Results: The values of the random forest model calibration results and observations were more condensed around the regression line y = 0.99x + 0.05, and the R squared value (R 2  = 0.98) was higher than that for the linear regression (R 2  = 0.87). The random forest model showed better performance than the traditional linear regression model., Conclusions: Our study provided an effective calibration method to support the accuracy of low-cost monitors. The machine learning method based on the calibration model established in our study can increase the effectiveness of future air pollution and health studies., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Despite their importance as sources of ecosystem services supporting the livelihoods of millions of people, forest ecosystems have been changing into other land use systems over the past decades across the world. While forest cover change dynamics have been widely documented in various ecological systems, how these changes affect ecosystem service values has received limited attention. In this study we assessed the impact of land-use/land-cover dynamics on ecosystem service values in dry Afromontane forest in Northern Ethiopia. We estimated ecosystem service values and their changes based on the benefit transfer method using land cover data of the years 1985, 2000, and 2016 with their corresponding locally valid value coefficients and from the Ecosystem service valuation database. The total ecosystem service values of the whole study area were about USD 16.6, 19.0, and 18.1 million in 1985, 2000, and 2016, respectively. The analyses indicated an increase in ecosystem service values from 1985 to 2000 and a decrease in ecosystem service values from 2000 to 2016. Similarly, the contribution of specific ecosystem services increased in the first study period and decreased in the second study period. The findings highlight how forest cover dynamics can be translated into changes in ecosystem service values in dry Afromontane forest ecosystems in Northern Ethiopia and showed how specific ecosystem services contributed to the observed trends. The findings also illustrated the temporal heterogeneity in the impacts of land-use/land-cover dynamics on values of ecosystem services. The findings can serve as crucial inputs for policy and strategy formulations for the sustainable use and management of forest resources and can also guide the allocation of limited resources among competing demands to safeguard the ecosystems that offer the best-valued services.

The plausibility of data from networks of low-cost measurement devices is a growing and important contentious issue. Informal networks of low-cost devices have particularly come to prominence for air quality monitoring. The contentious point is the believability of data without regular on-site calibration, since this is a specialist task and the costs very quickly become much larger than the cost of installation in the first place. This Sensor Issues suggests that approaches to the problem that involve appropriate use of independent information have the potential to resolve the contention. Ideas are illustrated particularly with reference to low-cost sensor networks for air quality measurement.

Heavy metal pollution in soils of development zones has attracted wide attention. In this study, soil heavy metal pollution levels and health risks in 15 selected development zones in Shandong Province were investigated for the first time. Geo-accumulation and potential ecological risk indexes were used to assess pollution levels, and health risk was assessed using the US Environmental Protection Agency model. The soil was contaminated by various heavy metals, among which Hg was dominant. A total of 19% of the monitoring sites showed moderate ecological risk level, and low risk level was observed in general. Pollution control of Hg and Cd in each development zone must be strengthened. Health risk analysis showed that noncarcinogenic and carcinogenic risk levels for adults and children were acceptable or nearly acceptable. Positive matrix factorization model was used to identify three possible sources of heavy metal pollution, namely, industrial sources, atmospheric deposition, and transportation. Some specific measures should be taken to prioritize the control of Hg, As, and Cr for protecting the soil environment and human health, especially vulnerable groups, such as children.

Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practical approach to measure and model air pollution concentration levels. In this study, we developed LUR models for street-level fine particulate matter (PM 2.5 ) concentration levels in Seoul, South Korea. 169 h of data were collected from an approximately three week long campaign across five routes by ten volunteers sharing seven AirBeams, a low-cost ($250 per unit), smartphone-based particle counter, while geospatial data were extracted from OpenStreetMap, an open-source and crowd-generated geographical dataset. We applied and compared three statistical approaches in constructing the LUR models - linear regression (LR), random forest (RF), and stacked ensemble (SE) combining multiple machine learning algorithms - which resulted in cross-validation R 2 values of 0.63, 0.73, and 0.80, respectively, and identification of several pollution 'hotspots.' The high R 2 values suggest that study designs employing mobile sampling in conjunction with multiple low-cost air quality monitors could be applied to characterize urban street-level air quality with high spatial resolution, and that machine learning models could further improve model performance. Given this study design's cost-effectiveness and ease of implementation, similar approaches may be especially suitable for citizen science and community-based endeavors, or in regions bereft of air quality data and preexisting air monitoring networks, such as developing countries., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Information on community structure and spatial distribution of benthic habitats are important in marine conservation and management. Coral areas, often monitored by trained scuba divers, are of importance for the ecosystem goods and services they provide. The data gathered may, however, be limited due to cost and time constraints. These restrictions and the continuing decline in coral reef health contribute to the need to develop rapid methods to efficiently document the distribution and status of coral reefs. A Rapid Assessment Instrument for Coastal Benthic Habitats (ARAICoBeH) System was developed to enable large-scale but low-cost coastal benthic habitat characterization and mapping without compromising accuracy. Inquiries on community structure and status in coral-dominated areas are also possible with the data collected using the method. The instrument, as well as the data processing and mapping algorithm are described in detail in this paper. A comparative study was conducted between ARAICoBeH and the frequently used underwater photo transect method. Variables compared were percent coral cover, functional group diversity, community structure as well as time and monetary requirements. There were no significant differences in estimates of percent coral cover and diversity of benthic functional groups for majority of sites while estimates of community structure were very similar. ARAICoBeH is cheaper and requires less time to gather the same amount of data as that of the photo transect method. The spatial distribution of coastal benthic habitats and community structure of coral-dominated areas in El Nido, Palawan, Philippines, are included to illustrate the application of the method.

This study is the first meta-regression analysis of the economic value of regulating ecosystem services at the global level. Most of the regulating ecosystem services have not been properly estimated in terms of economic value and are also ignored in the everyday decision-making process. This study has reviewed 100 publications and included 275 economic value estimates. This study includes explanatory variables in the meta-analysis to account for these influences on the estimated economic value of regulating ecosystem services. This study has estimated the economic value of regulating ecosystem services at US$29.085 trillion for 2015. This study also has found that the values of climate and water regulations are the highest contributors to the total value of regulating ecosystem services. This study indicates that the results of meta-analysis might be helpful to decision-making with respect to three aspects: first, planning and management of urban green cover for sustainable cities; second, integration of the economic value of all the regulating ecosystem services; third, budget allocation for conservation and improvement of regulating ecosystem services for the present and future generations.

A low-cost air sensor package was used to monitor indoor air quality (IAQ) in a classroom at the Albany Middle School in the San Francisco Bay Area of California. A rapid increase in carbon dioxide (CO 2 ) was observed in the classroom as soon as it is occupied. When the classroom is unoccupied, the CO 2 levels decay slowly toward the outdoor background level. All high CO 2 concentrations observed inside the classroom, above the outdoor background, was due to exhaling of the occupants. The CO 2 concentrations generally exceed the recommended level of 1000 ppb towards the end of the school day. The exceedances and slow decay may suggest that the ventilation rate in this school is not sufficient. The particulate level in the classroom was low until a distant wildfire advected large amount of particulate matter to the San Francisco Bay Area. Very high (10-15 times compared to the background) particle numbers (per m 3 of particles with diameter >0.3 µm) were observed in the classroom during the wildfire. These particles were relatively small (0.3-1.0 µm) and the filters (MERV 8) of the ventilation system were unable to filter them out. Therefore, the measurements made by low-cost particle counters can inform the school administrators of adverse IAQ during future wildfire (or other combustion) events. The particle number was independent of the occupation before and during the wildfire suggesting that all observed particles were infiltrated into the classroom from outside. Consistent with previous studies, no appreciable increase in the local ambient CO 2 background was observed during this distant wildfire event. Implications : Low-cost air sensors are effective in monitoring indoor air quality in classrooms. The CO 2 levels in classrooms are mainly generated indoors due to exhalation of occupants. Concentration of CO 2 generally exceed the recommended level of 1000 ppb towards the end of the school day. In contrast, the particulate matter mostly comes from outdoors and small particles penetrate though the filters normally used at schools. Distant wildfires do not increase the local CO 2 background appreciably, but significantly increase the particulate matter concentrations both indoors and outdoors. Further investigations are needed to assure that ventilation rates in classrooms are sufficiently health protective.

The need for continuous observation (1:1) of patients for safety precautions, including fall risk, elopement risk, confusion, and aggressive behavior, is highly variable, and it is therefore difficult to plan accurate staffing levels. The high variability in determining when 1:1 staffing for safety is indicated, and for how long, leads to resource strain and high cost to the hospital. A multidisciplinary team analyzed current processes for assigning, monitoring, and discontinuing safety 1:1 care for nonsuicidal patients using Six Sigma methodologies. The team implemented a standardized weaning process to reduce the duration of time on continuous observation and a standardized 4-hour reassessment using a behavior observation-tracking tool to validate the continued need for 1:1 coverage. The interventions resulted in reducing average monthly safety 1:1 staffing hours by 25.6% and saving an estimated $142 000 annually across 6 units. Phase 2 of the project integrated the observation-tracking tool and reassessment check-in into the hospital's electronic medical record for improved tracking and documentation.

European research efforts to address concerns in relation to increasing levels of marine litter and potential effects on ecosystems and human health have been launched. We assessed a total of 52 European projects which researched or contributed to the implementation of European marine litter legislation. These projects ranged from national initiatives, to large scale programmes involving multiple EU member states. The best represented topics within those European projects were 'Policy, Governance and Management' and 'Monitoring'. Comparatively 'Risk Assessment', 'Fragmentation' and 'Assessment Tools' were underrepresented. The analyses showed that West-European countries have contributed more to marine litter research and therefore received more funding. As a result, thematic hotspots were present, and scientific capacity is concentrated by topic and countries. The results indicate the need to continue to support initiatives to cover clearly identified gaps, either geographic or thematic, to deliver risk assessments and recommendations to address the marine litter issue., (Crown Copyright © 2019. Published by Elsevier Ltd. All rights reserved.)

Linking water to research on coupled human and natural systems (CHANS) has attracted wide interest as a means of supporting human-natural sustainability. However, most current research does not focus on water environmental properties; instead, it is at the stage of holistic status assessment and measures adjustment from the point of view of the whole study region without revealing the dynamic interaction between human activities and natural processes. This paper establishes an integrated model that combines a System Dynamics model, a Cell Automaton model and a Multiagent Systems model and exploits the potential of the combined model to reveal regions' human-water interaction status during the process of urban evolution, identify the main pollution sources and spatial units, and provide the explicit space-time measurements needed to enhance local human-natural sustainability. The successful application of the integrated model in the case study of Changzhou City, China reveals the following. (1) As the city's development has progressed, the water environment status in some spatial units is still unsatisfactory and may even become more serious, especially in the urban areas of the Urban District and Liyang County. The concentration of Chemical Oxygen Demand (COD) in monitoring section 157 of the Urban District has increased from 36.90 mg/l to 40.84 mg/l. The main source of this increase is the increase in secondary industry. (2) With the application of the spatially explicit measures of the sewage treatment ratio improvement and new sewage plant construction, the water quality in the urban area has significantly improved and now satisfies the water quality standards. The measure of livestock manure utilization enhancement is adopted to improve the spatial units in which livestock is the main pollution source and achieve the goal of water quality improvement. The model can be used to support the sustainable status assessment of human-water interaction and to identify effective measures that can be used to realize human-water sustainability along with social-economic development., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Air quality monitoring has traditionally been conducted using sparsely distributed, expensive reference monitors. To understand variations in PM 2.5 on a finely resolved spatiotemporal scale a dense network of over 40 low-cost monitors was deployed throughout and around Pittsburgh, Pennsylvania, USA. Monitor locations covered a wide range of site types with varying traffic and restaurant density, varying influences from local sources, and varying socioeconomic (environmental justice, EJ) characteristics. Variability between and within site groupings was observed. Concentrations were higher near the source-influenced sites than the Urban or Suburban Residential sites. Gaseous pollutants (NO 2 and SO 2 ) were used to differentiate between traffic (higher NO 2 concentrations) and industrial (higher SO 2 concentrations) sources of PM 2.5 . Statistical analysis proved these differences to be significant (coefficient of divergence > 0.2). The highest mean PM 2.5 concentrations were measured downwind (east) of the two industrial facilities while background level PM 2.5 concentrations were measured at similar distances upwind (west) of the point sources. Socioeconomic factors, including the fraction of non-white population and fraction of population living under the poverty line, were not correlated with increases in PM 2.5 or NO 2 concentration. The analysis conducted here highlights differences in PM 2.5 concentration within site groupings that have similar land use thus demonstrating the utility of a dense sensor network. Our network captures temporospatial pollutant patterns that sparse regulatory networks cannot.

Serious environmental problems have accompanied remarkable global economic growth for decades. To assist managers in the semiconductor industry with economic and environmental management, this study executes DuPont analysis to examine economic impacts from the effective implementation of sustainability initiatives. We propose a two-stage process including economic development efficiency and environmental protection efficiency through the dynamic data envelopment analysis (DDEA) to reflect the characteristics of eco-efficiency. Through DuPont analysis, the main finding shows the potential improvement in firms' return on equity (ROE) by efficiently utilizing assets to generate sales quickly.Relative to economic development efficiency, the firms show lower scores and higher standard deviations in the environmental protection ability, thus denoting a large gap in the level of environmental protection production technology. The findings in this study reveal that the financial foundations and sustainable development of industries should be improved simultaneously even though specific levels of semiconductor industrial eco-efficiency improvement vary among companies in Taiwan.

Economic development puts pressure on environment through air, water and land degradation, which in turn brings real costs to the economy. Actual economy growth should therefore consider the environmental degradation cost resulted from economic activities. Pearl River Delta (PRD) region as a typical delta area with rapid development in China, is with great significance to understand the loses resulted from environmental pollution. This study conducts an environmental economic accounting within the PRD region from 2011 to 2015 using the environmental degradation cost accounting approach. We identified and calculated the economic, agricultural, industrial and social losses resulting from air, water and waste pollution with different valuation methods, which includes shadow price, replacement costs, market value method, etc. The results showed the total environmental degradation cost ranged from 18.1 to 19.8 billion US$ and the environmental degradation index declined slightly over the years, with significant differences among cities. It implied that the environmental condition of PRD region has been continuously improved over the years, but the capacity of environment control between cities had large differences. Cities in PRD region should therefore take measures tailored to their current situation to optimize their resource endowment and industrial structure, to overcome the conflicts between economic development and environmental protection. For cities with relatively high degradation cost, it is urgent to accelerate the efforts in improving the quality of the environment and ecosystem. For cities with lower degradation cost, it is important to take actions to keep on a sustainable and ecological efficient developing path. MAIN FINDINGS: The total environmental degradation cost of the PRD region is firstly calculated with insights on environmental management., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Microplastics (MP) are detected in aquatic environments worldwide, yet detection is often limited to larger sized MP. To address this data gap, the abundance of MP 3-500 μm was assessed in the Los Angeles River, the San Gabriel River, and the Long Beach Harbor (CA, USA), three areas with highly urbanized surroundings. Whole surface water samples were taken, subjected to a hydrogen peroxide digestion and MP counts were compared between unstained visual examination and Nile Red staining identification techniques. The largest concentration of MP was found in the Los Angeles River, where 13,622 MP m -3 were found using unstained visual examination and 641,292 MP m -3 were found utilizing Nile Red staining. The protocol used to detect smaller sized MP is low cost, time efficient, and reproducible. This work highlights the need for more extensive sampling of smaller sized MP globally and universal testing and reporting standards for MP detection., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Aims: To evaluate a low-cost water quality test for at-scale drinking water safety estimation in rural India., Methods and Results: Within a longitudinal study to characterize variability in household drinking water safety in rural Maharashtra, we piloted a low-cost presence-absence (LCPA) microbial test designed to be used by volunteer residents in rural areas. In comparing the LCPA results with standard laboratory methods for enumeration of Escherichia coli, we found that LCPA tests using modified mTec media were highly sensitive in detecting drinking water of moderate risk (88% of tests were positive at E. coli counts of 11-100 CFU per 100 ml) and high risk (96% of tests were positive at E. coli counts of 101 + CFU per 100 ml). The LCPA tests demonstrated low specificity for E. coli specifically, due to concurrent detection of Klebsiella: 38% of LCPA tests were positive even when E. coli was not detected in a 100 ml sample by membrane filtration, suggesting the test would be conservative in risk estimation. We also found that 47% of participants in rural villages in India were willing to conduct tests and return results after a brief training, with 45% of active participants sending their water testing results via short message service., Conclusions: Given their low cost (~US$0.50 as piloted) and open-source format, such tests may provide a compelling alternative to standard methods for rapid water quality assessments, especially in resource-limited settings., Significance and Impact of the Study: The lack of availability of water quality data constrains efforts to monitor, evaluate and improve the safety of water and sanitation infrastructure in underserved settings. Current water testing methods are not scalable because of laboratory and cost constraints. Our findings indicate the LCPA or similar low-cost microbial tests could be useful in rapid water safety estimation, including via crowdsourcing., (© 2019 The Society for Applied Microbiology.)

Bohai Bay, in the western region of northeastern China's Bohai Sea, receives water from large rivers containing various pollutants including dioxin-like compounds (DLCs). This study used the established zebrafish (Danio rerio) model, its known developmental toxicity endpoints and sensitive molecular analyses to evaluate sediments near and around an industrial effluent site in Bohai Bay. The primary objective was to assess the efficacy of rapid biological detection methods as an addition to chemical analyses. Embryos were exposed to various concentrations of sediment extracts as well as a 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD) positive control. Exposure to sediment extract nearest the discharge site (P1) resulted in the most severe- and highest rates of change in embryos and larvae, suggesting that DLC contaminated sediment probably did not occur much beyond it. P1 extract resulted in concentration dependent increases in mortality and pericardial edema. Its highest concentration caused up-regulation of P-450 (CYP)-1A1(CYP1A) mRNA expression at 72 h post fertilization (hpf), an increase in its expression in gill arches as observed by whole mount in situ hybridization, and an increased signal in the Tg(cyp1a: mCherry) transgenic line. The pattern and magnitude of response was very similar to that of TCDD and supported the presence of DLCs in these sediment samples. Follow-up chemical analysis confirmed this presence and identified H7CDF, O8CDF and O8CDD as the main components in P1 extract. This study validates the use of biological assays as a rapid, sensitive, and cost-effective method to evaluate DLCs and their effects in sediment samples. Additionally, it provides support for the conclusion that DLCs have limited remobilization capacity in marine sediments., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The Mobile Crowd-sensing Network is a novel cyber-physical-social network which has received great attention recently and can be used as a powerful tool to monitor the phenomenon of the field of interest. Due to the limited budget, how to choose appropriate participants to maximize the coverage quality is one of the most important issues when the mobile crowd-sensing network applies to practical application, such as air quality monitoring. In this paper, given the number of available participants, the traverse path and the reward of each participant, we investigate the problem of how to choose suitable participants to monitor an environment of a critical region by a crowd-sensing network, while the total rewards for all selected participants is not larger than the limited budget. In our solution, we first divide a big critical region such as a city into smaller regions of different size, and select some sampling points in the smaller region; the collected data of those sampling points represents the collected data of the whole smaller region. Then, we design a greedy algorithm to select participants to cover the maximum sampling points while the total rewards of selected participants does not exceed the limited budget. Finally, we evaluate the validity and efficiency of the proposed algorithm by conducting extensive simulations. The simulation results show that the greedy algorithm outperforms an existing scheme.

Enriched and bio-refractory soil heavy metals (SHMs) originate from the underground mineral, which supplies energy and materials for the development of economy and industry. Investigating soil metal contents and their adverse health impacts is the principal concern associated metal contaminated industrial areas, including both current assessments and future projections. In this research, we create a novel spatiotemporal model of SHMs prediction and risk characterization for future by citing a rigorous theory of industrial economics, and time series of activity intensity changes of various pollution sources are forecasted. The dynamic change of source contributions is quantitatively resolved and the mean SHMs concentrations are estimated by classical formulas for heavy metal accumulation. Human health risk in the future is described in a manner of time series. The results of the case study show that contribution rates of the five sources of the six metals change continuously over time. Pb, Cd and As assume the highest growth rates (400%, 500% and 165%), while Zn, Ni, Cr possesses relatively lower growth (< 130%), compared to their corresponding background values. Health risk of local sensitive population (children) is estimated at exceeding threshold in 2022 (non-carcinogenic) and 2012 (carcinogenic), and the upward trend will continue. Traffic emission, agriculture and household garbage are identified as major risky sources in the coming decades at the studied area, and improvement measures are recommended. Although a degree of uncertainties exists, the overall tendency is a conservative bias for chemical risk. Additionally, this paper is the first to explore a methodology of predicting future SHMs and associated human health risk, based on industrial economics and temporal source apportionment., (Copyright © 2018. Published by Elsevier Inc.)

Natural ecosystems benefit human lives via providing fundamental life-support services and goods upon which human civilization depends. However, as nature provides those for free, many people believe that they are of little or no value and they exploit the land greedily and unreasonably, which makes serious ecological degradation. Concerning this issue, we present the ecological services valuation model (ESVM) to measure the cost of environmental degradation of land use cost, which is an evaluation model of environmental degradation cost. Environmental degradation cost refer to the cost of deterioration or compromise of natural environment through natural processes or human activities, which consists of opportunity cost and environmental damage cost. Land area is an important variable in the ESVM. Based on Osmotic system, we put forward the effective land area, which combines the scale factor and the impact of external environment. What is more, the Cobb-Douglas production function is modified to establish the model. Finally, we propose the calculation formula of the economic cost of land use projects. Analysis of effectiveness and sensitivity prove that ESVM was a relatively stable model.

Environmental DNA (eDNA) has been used to record the presence of many different organisms in several different aquatic and terrestrial environments. Although eDNA has been demonstrated as a useful tool for the detection of invasive and/or cryptic and declining species, this approach is subject to the same considerations that limit the interpretation of results from traditional survey techniques (e.g. imperfect detection). The wood turtle is a cryptic semi-aquatic species that is declining across its range and, like so many chelonian species, is in-need of a rapid and effective method for monitoring distribution and abundance. To meet this need, we used an eDNA approach to sample for wood turtle presence in northern Virginia streams. At the same time, we used repeat visual encounter surveys in an occupancy-modelling framework to validate our eDNA results and reveal the relationship of detection and occupancy for both methods. We sampled 37 stream reaches of varying size within and beyond the known distribution of the wood turtle across northern Virginia. Wood turtle occupancy probability was 0.54 (0.31, 0.76) and while detection probability for wood turtle occupancy was high (0.88; 0.58, 0.98), our detection of turtle abundance was markedly lower (0.28; 0.21, 0.37). We detected eDNA at 76% of sites confirmed occupied by VES and at an additional three sites where turtles were not detected but were known to occur. Environmental DNA occupancy probability was 0.55 (0.29, 0.78); directly comparable to the VES occupancy estimate. Higher probabilities of detecting wood turtle eDNA were associated with higher turtle densities, an increasing number of days since the last rainfall, lower water temperatures, and lower relative discharges. Our results suggest that eDNA technology holds promise for sampling aquatic chelonians in some systems, even when discharge is high and biomass is relatively low, when the approach is validated and sampling error is quantified., Competing Interests: The authors have declared that no competing interests exist.

Currently, low-cost, sensor-based fine dust measurement devices are commercially available in South Korea. This study evaluated the reliability of three such devices-Yi Shan A4, Plantower PMS7003, and Plantower PMS7003-in comparison to long-term consecutive monitoring systems for discharge and prevention facilities regarding fine dust control. The performance of these devices for concentration intervals over time was examined through real-time comparison using a GRIMM (Model: 11-A, dust spectrometer from Grimm Technologies) as a reference; this included a correction factor (C-Factor), calculated by a gravimetric method and an equivalence test. For comparison, the reference and target devices were installed in a chamber with fine dust concentrations of 2 µg/m 3 , with temperature and humidity maintained at 20 °C and 40%, respectively. The fine particulate matter (PM) 2.5 concentrations were classified into five intervals: ≤40 µg/m 3 , 40⁻80 µg/m 3 , 80⁻120 µg/m 3 , 120⁻160 µg/m 3 , and 200⁻230 µg/m 3 . Statistical analysis was performed using data obtained from national stations for monitoring and controlling fine dust released from facilities under high fine dust loading conditions. The results showed that the measurements of all target devices, which were corrected according to the reference device, provided accurate values at PM 2.5 concentrations of ≥40 µg/m 3 . The statistical analysis results suggest that the evaluated devices are more reliable than the conventional numerical-analysis-based monitoring system.

Environmental⁻economic efficiency assessment is an effective way to evaluate the degree of coordination between an economy and the environment. Previous studies on environmental⁻economic efficiency have primarily investigated the efficiency of economic production and have often overlooked the efficiency of pollution treatment in overall economic activities. We applied a network data envelopment analysis model to evaluate the environmental⁻economic efficiency of a multistage process with undesirable outputs in 30 Chinese provinces during 2001⁻2017. The multistage process consisted of two sequential stages: economic production and pollution treatment. The results show that the average environmental⁻economic efficiency across all provinces was generally low but demonstrated a gradual upward trend during the study period. The spatial pattern for the 30 provinces showed that provinces with medium or high environmental⁻economic efficiency are mainly located in the eastern regions in China. Finally, few provinces exhibited economic activities with high economic production and pollution treatment efficiency, with most provinces generally having low economic production and pollution treatment efficiency. Hence, provinces with different economic production and pollution treatment efficiency modes should implement targeted improvement strategies according to their characteristics.

Communities of nonvascular cryptogams, such as mosses or lichens, are an important part of the Earth's biodiversity, contributing to the regulation of the carbon and nitrogen cycles in many ecosystems. Being poikilohydric organisms, they do not actively control their internal water content and need a humid environment to activate their metabolism. Therefore, studying water relationships of nonvascular cryptogams is crucial to understand both their diversity patterns and their functions in the ecosystems. We present the BtM datalogger, a low-cost open-source platform for the study of the water content of nonvascular cryptogams. The datalogger is designed to measure ambient temperature, humidity, and conductance from up to eight samples simultaneously. We provide a design for a printed circuit board (PCB), a detailed protocol to assemble the components, and the required source code. All this makes the assembly of the BtM datalogger accessible to any research group, even to those without previous specialized knowledge. Therefore, the design presented here has the potential to help popularize the use of this type of device among ecologists and field biologists.