Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia.

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.

Cost-effective surveillance of invasive species using info-gap theory.

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.

Mapping pollution exposure and chemistry during an extreme air quality event (the 2018 Kilauea eruption) using a low-cost sensor network.

Extreme air quality episodes represent a major threat to human health worldwide but are highly dynamic and exceedingly challenging to monitor. The 2018 Kilauea 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 (SO2) 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 SO2 during the event. Downwind of the eruption, network stations measured peak hourly PM2.5 and SO2 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 SO2 Additionally, the spatially distributed network was able to resolve the volcanic plume's chemical evolution downwind of the eruption. Measurements find a mean SO2 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.

Emergency deployment of direct air capture as a response to the climate crisis.

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 CO2 removal, and climate impacts. An emergency DAC program, with investment of 1.2-1.9% of global GDP annually, removes 2.2-2.3 GtCO2 yr-1 in 2050, 13-20 GtCO2 yr-1 in 2075, and 570-840 GtCO2 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 CO2 emissions (to 2085-2095) and peak warming (to 2090-2095); yet warming still reaches 2.4-2.5 °C in 2100. Such massive CO2 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.

A new approach for the determination of sunscreen levels in seawater by ultraviolet absorption spectrophotometry.

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.

Fiscal Expenditures on Science and Technology and Environmental Pollution: Evidence from China.

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 (SO2) emissions, wastewater emission, and atmospheric particulate matter less than 2.5 micrometers in diameter (PM2.5). 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 (SO2) emissions and PM2.5 concentrations, but fail to alleviate wastewater emissions. Specifically, for every 1% increase in FESTs, SO2 emissions were reduced by 5.317% and PM2.5 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.

Spatiotemporal changes caused by the intensive use of sea areas in the liaoning coastal economic zone of China.

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.

Exploring Evaluation Variables for Low-Cost Particulate Matter Monitors to Assess Occupational Exposure.

(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/m3 PM2.5, 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.

Ecological status of a freshwater tectonic lake of the indo-burmese province: Implications for livelihood development.

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.

Disposable and Low-Cost Colorimetric Sensors for Environmental Analysis.

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.

Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM2.5 Measurement Using Low-Cost Sensors.

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 (PM2.5). 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 PM2.5 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/m3 with the highest PM2.5 period average concentration of 91 µg/m3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m3 measured in Faraja, The Gambia. Kampala in Uganda and Nnewi in Nigeria recorded the longest periods with concentrations >250µg/m3. 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 PM2.5 concentrations in SSA countries. Such data are crucially needed to raise public, societal and policymaker awareness about air pollution across SSA.

An integrated system of air sampling and simultaneous enrichment for rapid biosensing of airborne coronavirus and influenza virus.

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/m3 (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).

Microplastic Prevalence in 4 Oregon Rivers Along a Rural to Urban Gradient Applying a Cost-Effective Validation Technique.

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.

Freshwater budget in the Persian (Arabian) Gulf and exchanges at the Strait of Hormuz.

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.

Low-Cost Sensors for Urban Noise Monitoring Networks-A Literature Review.

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.

Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile.

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 (PM10 and PM2.5) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM10-PM2.5 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 PM2.5 (normalized root-mean-square error 9-24%) and PM10 (10-37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM2.5 (R2 0.47-0.86) than PM10 (0.24-0.56). The correlations (R2) between the 24-h PM2.5 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 PM2.5 averages after correcting for RH.

Extensive evaluation and classification of low-cost dust sensors in laboratory using a newly developed test method.

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 PM1 , PM2.5 , and PM10 were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM1 and PM2.5 , 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 PM10 measurements. The 32, 24, and 16% of all the tested sensors for PM1 , PM2.5 , and PM10 measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM10 measurement was relatively less satisfactory.

Examining the functional range of commercially available low-cost airborne particle sensors and consequences for monitoring of indoor air quality in residences.

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/m3 . At greater concentrations, sensor output deviates from linearity at approximately 300-3000 µg/m3 . 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.

Contribution of low-cost sensor measurements to the prediction of PM2.5 levels: A case study in Imperial County, California, USA.

Regulatory monitoring networks are often too sparse to support community-scale PM2.5 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 PM2.5 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 PM2.5 prediction. We adopted the Random Forest algorithm to estimate daily PM2.5 concentrations at a 1-km spatial resolution using three different PM2.5 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 PM2.5 prediction with an increase of cross-validation (CV) R2 by ~0.2. The IVAN measurements also contributed to the increased importance of emission source-related covariates and more reasonable spatial patterns of PM2.5. 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.

Validation and application of cost and time effective methods for the detection of 3-500 µm sized microplastics in the urban marine and estuarine environments surrounding Long Beach, California.

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.