Bureau Of Management Research Articles

Mapping migration habitat for western monarch butterflies reveals need for public-private approach to conservation

IntroductionIdentifying habitat of migratory species to effectively support conservation and management requires careful consideration of (1) the data used to inform habitat models, (2) the biology of the organism, (3) land tenure, and (4) the needs of the target audience.MethodsTo provide this information for western U.S. monarch butterflies, a population undergoing decline, we modeled habitat during the spring and fall migrations. Our approach controlled for biases in citizen science locality data, the principal source of monarch observation data, and incorporated needs for milkweed host plants in the spring and nectar plants in the fall.Results and DiscussionThe results showed the distribution of habitat for spring and fall migration, where the Coast Range and Central Valley in California and riparian areas throughout the range were particularly important. Just 29% of predicted habitat for spring and fall migrations, combined, overlapped between the two seasons. Although the U.S. federal government manages 53% of the land in the western U.S., government land makes up just 11.7% of the spring migration range and 23.5% of the fall migration range. State and local governments and non-governmental organizations (NGOs) manage an additional 4.2% of the spring and 4.0% of the fall migration habitat. Thus, like eastern monarchs, western monarchs rely heavily on land under private ownership for their migration and to be successful, monarch conservation efforts must embrace a public-private approach. Among federal agencies, the Bureau of Land Management (BLM; 5.9% of spring and 9.7% of fall habitat) and Forest Service (3.3% of spring and 9.2% of fall habitat) manage the greatest shares. Less than half of the government and NGO owned habitat for both migrations is managed for biodiversity conservation rather than multiple uses (spring, 46.0%; fall, 36.5%). We created custom model outputs for the BLM to highlight areas of both regional and local importance for migrating monarchs in each BLM administrative unit, enabling managers across the agency to contribute to recovery. The outcomes provide input at a relevant spatial scale to support actions such as habitat restoration, riparian zone protection, and pesticide use reduction to enhance conditions for migrating monarchs on both government and private lands.

Mapping Phosphorus Concentration in Lake Mainit, Philippines Using Landsat 8 OLI and GIS Techniques

Abstract. Lake Mainit is the fourth largest lake in the Philippines and water is one of the most important natural resources for humans and other living organisms. Sensors on satellites can measure the amount of solar radiation absorbed by surface water at different wavelengths, which can be compared with parameters of water quality. This study explored the use of Landsat 8 Operational Land Imager (OLI) and Geographic Information System (GIS) techniques for assessing the Phosphorus (P) content in the lake. Water quality data of Phosphorus from Environmental Management Bureau (EMB) was utilized to correlate with spectral values. Linear forward regression results yielded significant correlation with band combination B2/B4 with an R2 of 55% for Phosphorus (P). The model was then used to map the P content in the lake and was found out that the concentration ranges from 0.0228768 mg/L to 0.23145 mg/L. The study was effective in correlating P content and the bands of Landsat 8 OLI. In addition, GIS techniques were used in extracting spectral values of bands.

The responses of the supply and demand sides of new energy vehicles to subsidy removal: Empirical evidence from China

The policy-driven development of China’s new energy vehicle (NEV) has been accompanied by significant fluctuations in the industrial chain due to the substantial fiscal subsidy removal. The study aims to examine the impact that three typical fiscal subsidy removal events enacted by China’s government have on various segments of the NEV industrial chain. The three events were enacted in 2016 (a 20% reduction and a limit for local subsidies), 2018 (raising the threshold, no subsidies for range below 150 km, and a 4-month transitional period), and 2019 (a 50% reduction, full cancelation of local subsidies, and a 3-month transitional period). This is done by applying the event study method and a difference-in-difference framework to finance data from capital market and sales data traffic management bureau. Empirical evidence suggests that, on the supply side, the three removal policies have caused various negative influences on companies involved in the industrial chain, with the midstream (e.g. battery, motor, and electric control) being the component of the chain affected the most by the policy removal. On the demand side, the events in 2016 and 2019 have decreased the vehicle sales in NEV pilot cities nationwide. Rather than discouraging consumer purchases, however, the event in 2018 has counter-intuitively boosted vehicle sales due to proper establishment of the transitional period (in comparison to 2019) of the policy. Further, NEV sales in cities with small population are found to be more dependent on government fiscal subsidies. We offer management suggestions and make policy recommendations for subsidy removal.

Large offshore wind farms have minimal direct impacts on air quality

Abstract Wind power has rapidly grown over the past decade because it is clean, renewable, and abundant. However, wind farms can affect local weather and possibly alter the transport, diffusion, and concentration of air pollutants. Given the unprecedented expansion of offshore wind farms planned along the U.S. East Coast by the Bureau of Ocean Energy Management (BOEM), this study aims to investigate if and how those future offshore wind farms might directly affect air pollution along the densely populated East Coast, in particular, the concentrations of ozone (O3), fine particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2). These pollutants are regulated at the federal and state levels and are harmful to human health. We exclusively study the direct effects of the wind turbines on air pollution (via meteorological changes), rather than investigating the indirect impacts of replacing fossil-fuel power plants with wind farms. We first run a numerical meteorological model, the Weather Research and Forecast (WRF) model, to simulate the meteorology along the U.S. East Coast during the summer of 2018 in two scenarios, with and without the wind farms. Then we use the output of these two sets of simulations from the WRF model as input to the Comprehensive Air Quality Model with extensions (CAMx) to simulate the changes in air quality in the study domain due to the wind farms. On average, we find a minor increase in O3 levels within the wake of the New Jersey WEA. The minor changes to O3 can be attributed to the slight temperature increase below the turbine hub height, within the rotor area, as well as a significant decrease in wind velocity in the wake of the turbines and a slight increase in VOCs. In addition, we report that the other three pollutants remain unchanged in the presence of wind farms. In summary, the direct impacts on air pollution by the BOEM-planned offshore wind farms are expected to be negligible.

Standardization of Turbine Design and Installation Vessels to Accelerate the Offshore Wind Industry in the United States

Offshore wind energy has gained attention as a promising renewable energy source with many benefits, including clean, sustainable, and scalable electricity production. Despite the vast potential for offshore wind production in the United States, the country lags in its development. The industry struggles with supply chain challenges related to the complex logistics around the design and construction of many component parts, installation and maintenance vessels, and shipyards that can accommodate the massive turbine components before installation. These challenges are complicated by the rapid increase in size of offshore wind turbines to achieve higher power generation, which are not easily handled by other parts of the supply chain. The US lacks access to wind turbine installation vessels (WTIVs), particularly those that can install very large turbines. To address these issues, we propose policy options to the US Bureau of Ocean Energy Management of the Department of Interior and the US Department of Energy to spearhead standardization in this sector of the economy by exploring standardization of maximum turbine size, investment in WTIVs, or allowance of unrestricted or market-driven offshore wind farm development. These options have great potential to enable growth in the offshore wind energy sector in the US and achieve the federal government's goal of 30 GW of offshore wind energy by 2030.

Carbon stock assessment of a reforestation site within Mt. Arayat protected landscape, Pampanga, Philippines

The Philippines has very few studies in terms of biomass production and carbon stocks in reforestation sites and the level of emission that has been avoided due to forest protection activities. Most of carbon stock estimates being used in the country are based on secondary data or studies in other countries using the same species. The study aimed to provide a reliable assessment on the contribution of reforestation sites in biomass production and carbon stocks and the potential of these plantation to contribute to the climate change mitigation efforts in the Philippines. The guideline prepared by the Philippines’ Department of Environment and Natural Resources – Forest Management Bureau (DENR-FMB) in 2021 on Forest Resources Assessment (FRA) which follows the manual of Food and Agriculture Organization of the United Nations (FAO) Forestry Department in conducting FRA was used during data collection. A tract was established in the southern portion of the reforestation site wherein the species planted in 2012 are already very prominent and their diameter at breast height (DBH) and total height were measured and their corresponding wood specific gravity were taken into account. Carbon stocks were estimated using Chave et al.’s and Brown’s allometric equations. The estimated carbon stocks using Chave et al.’s formula is 542.3 tC/ha while the estimated carbon stock using Brown’s formula is 2001.6 tC/ha. The results of computation using Brown’s equation are considerably higher than the results using Chave et al.’s equation considering that Brown’s equation only took into consideration the DBH of trees while Chave et al.’s equation included the height and wood specific gravity of each species. The study demonstrated how important our forests in terms of their roles as carbon sinks and therefore contribute to our country’s efforts in climate change mitigation.

Free‐roaming horses exceeding appropriate management levels affect multiple vital rates in greater sage‐grouse

AbstractSince the passage of the Wild Free‐Roaming Horses and Burros Act of 1971, federal agencies have been responsible for managing free‐roaming equids in the United States. Over the last 20 years, management has been hampered by direct opposition from advocacy groups, budget limitations, and a decline in the public's willingness to adopt free‐roaming horses (Equus caballus). As a result, free‐roaming equid numbers have increased to >3 times the targeted goal of 26,785 (horses and burros [E. asinus] combined), the cumulative sum of the appropriate management levels (AML) for all 177 designated herd management areas (HMA) managed by the Bureau of Land Management. This increase is one of the causes of greater sage‐grouse (Centrocercus urophasianus) population declines, owing to habitat alteration from free‐roaming equids exacerbated by ongoing drought. To evaluate potential demographic mechanisms influencing these declines, we compiled survival data from 4 studies in central Wyoming, USA, including 995 adult female (first‐year breeders or older) sage‐grouse during the breeding season, 1,075 nests, 372 broods, and 136 juveniles (i.e., overwinter survival for fledged young), from 2008–2022. During this period, we also obtained population information for free‐roaming horses from 9 HMAs used by individual grouse in our sample. Population estimates of free‐roaming horses for these HMAs ranged from 59% to 7 times of the maximum appropriate management level (AMLmax). Sage‐grouse monitored outside of HMAs represented control populations and, because we assumed they were not exposed to populations of free‐roaming horses, we set values of AMLmax to zero for all grouse located outside of HMAs. To evaluate whether free‐roaming horses were negatively affecting sage‐grouse, we modeled daily survival of breeding age females, nest, broods, and juveniles. There was strong or moderate evidence that overabundant free‐roaming horses negatively affected nest, brood, and juvenile survival. When horse abundance increased from AMLmax to 3 times AMLmax, survival was reduced 8.1%, 18.3%, 18.2%, and 18.2% for nests, early broods (≤20 days after hatch), late broods (>20 days to 35 days after hatch), and juveniles, respectively. These results indicate increasing free‐roaming horse numbers affected vital rates for important life stages of sage‐grouse, and that maintaining free‐roaming horse numbers below AMLmax would reduce negative effects to sage‐grouse populations.

Development of the National Cooling Action Plan of the Philippines

Abstract The Philippines NCAP was developed to account for the environmental impacts of energy consumption (indirect impacts) and use of high-GWP refrigerants (direct impacts) from the RAC Sector that can be mitigated by transitioning to more climate-friendly and higher-efficiency refrigerants. Utilizing the NCAP Methodology developed by the UNEP-led Cool Coalition, UN ESCAP in collaboration with Alliance for an Energy Efficient Economy (AEEE) together with and built on the expertise of the Cool Coalition’s NCAP Working Group facilitated by The Kigali Cooling Efficiency Programme (K-CEP), the Philippines NCAP was launched by the Philippines Department of Energy – Energy Utilization and Management Bureau, Department of Environment and Natural Resources, and United Nations Development Programme (Philippines Country Office). This paper presented the Reference Cooling Scenario (RCS) and the Sustainable Cooling Scenario (SCS) adopted from the business-as-usual (BAU) and Clean Energy Scenario (CES) of the Philippine Energy Outlook. With these assumptions on RCS and SCS, the domestic refrigeration sector will save 4.41 TWh while the residential cooling sector will save 12.15 TWh. There is a net effect in total emission reduction estimates of 10.68 MT CO2 equivalent which is close to 12 % of the unconditional target submitted to UNFCCC.

Spatiotemporal distribution of sediment waves in the northern Gulf of Mexico Basin, USA

The northern Gulf of Mexico basin, known for its hydrocarbon potential and a myriad of geologic structures and processes, has been underexplored to understand deepwater sediment waves. The recent release of a vast amount of both 2D and 3D seismic data by the Bureau of Ocean Energy Management (BOEM) calls for a basin-wide identification of the sediment waves in the Gulf of Mexico.Integrating seismic, well-log, and high-resolution bathymetric data, this study identified sediment-wave fields on the seafloor as well as in the stratigraphic record. These sediment waves have an average wavelength of 798 m and an average wave height of 18 m. On the present-day seafloor, sediment waves are only located on the northwestern continental slope and eastward of the Bryant Fan area (south of Green Knoll). However, in the stratigraphic record, these bedform structures were found to be prevalent across the northwestern continental slope, northeastern continental slope, and continental rise. All of these sediment waves migrate upslope with crests that are perpendicular to the direction of basin-slope (i.e., parallel to the bathymetric contours). Thus, they are interpreted as cyclic-steps bedforms produced by supercritical sediment gravity flow processes. Investigations of these sediment waves have implications for petroleum geology, geohazard studies, oceanography, hydrodynamics, paleoclimate, and coastal engineering.

Expert-driven geothermal play fairway analysis for low to medium temperature hidden systems in northwestern Luzon Island, Philippines

The Philippines is the third largest geothermal power-producing country in the world. However, additional opportunities exist to expand the geothermal portfolio of the country with the exploitation of low- and moderate- temperature resources, as well as assessment and development of hidden geothermal systems (i.e., those with no active surface manifestations). As part of the Geothermal Development Initiative (GEODE) funded through the U.S. Department of State award to the University of Nevada, Reno, a collaboration between the Philippines Renewable Energy Management Bureau (REMB) of the Department of Energy and the University of Nevada in Reno, Great Basin Center for Geothermal Energy occurred from September 2022 to March 2024. As part of this collaboration, an expert-driven geothermal Play Fairway Analysis (PFA) was conducted in the northwestern portion of Luzon Island of the Philippines utilizing existing data sets available to the REMB. The goal of this PFA is to identify areas with greater relative geothermal favorability, determine where the data gaps are, and assist in the discovery of hidden geothermal systems. A geothermal PFA requires the compilation and transformation of datasets into appropriate formats (e.g., tables, shapefiles, and raster files) and evaluation of each dataset to determine how it can be used as a proxy for the key attributes of a geothermal system (e.g., heat and permeability). Once the data are organized, they are weighted for integration into the GIS software to develop a favorability model for heat and permeability. The attribute models are then combined to produce two PFA models: the conventional hydrothermal low- to moderate- temperature geothermal favorability and the hidden systems favorability. The data difference between the conventional geothermal favorability and hidden systems models is that hot springs are not used for the hidden systems model. The conventional favorability model of northwestern Luzon Island indicates areas of higher geothermal favorability in the central and southern sections of the study area. Many of the favorable areas identified in the conventional model already have active leases for geothermal exploration, lending more confidence to the methodology and model, and suggesting that the areas with no current leases and high geothermal favorability could represent future exploration targets. The hidden systems model shows favorable zones in the north, central and southern sectors, and can serve as a tool to decide the areas for exploration of potential hidden geothermal systems, particularly, in the Ilocos Norte, Apayao, and Nueva Viscaya regions.

Evaluating mountain lion diet before and after a removal of feral horses in a semiarid environment

AbstractNon‐native species can affect ecosystems by influencing native predator‐prey dynamics. Therefore, management interventions designed to remove non‐natives may inadvertently lead to increased predation on native species. Feral horses are widely distributed throughout the arid parts of western North America. A growing body of research indicates that horses can be an important prey species to mountain lions in ecosystems where they overlap. In December 2020, the Bureau of Land Management removed 455 horses from the Delamar Mountains, Nevada, USA. We leveraged this management intervention to implement a before–after–control–impact study to test hypotheses about predation on horses and native ungulates. We predicted (1) that horses would comprise an important part of the diet in this mixed‐prey community, (2) following removal, the proportion of horses in the diet would decrease and native ungulates would increase, and (3) mountain lion home ranges overlapping the treatment areas would increase in response to decreased prey availability. From 2018 to 2022, we investigated 1360 clusters from 29 GPS‐collared lions and identified 1056 prey items. To model the probability of a predation event (a kill), we fit a mixed‐effects logistic regression model for ungulate prey as a function of lion sex, treatment area (in/out), and treatment period (pre‐/post‐removal). We used a log‐linear regression model to evaluate changes in home range size. The most common prey were mule deer (55%), feral horses (32%), and coyotes (4%). Twenty‐two of 29 lions consumed horses, although the rate of horse consumption was highly variable across individuals. Horses of both sexes and all age classes were predated. In contrast to predictions, our models detected no effect of removals on diet composition (βinteraction = 0.30 ± 1.1), nor did the removal influence home range size (βinteraction = 0.02 ± 0.02). Despite a 46% reduction in horse abundance, we found no evidence for prey‐switching following the horse removal treatment. Removal magnitude, rapid horse immigration, and/or behavioral specialization of individual mountain lions may help explain these results. Our findings have important implications for mountain lion and feral horse management in arid environments characterized by high prey diversity, but low prey abundance.

An improved transformer‐based model for long‐term 4D trajectory prediction in civil aviation

AbstractFour‐dimensional trajectory prediction is a crucial component of air traffic management, and its accuracy is closely related to the efficiency and safety of air transportation. Although long short‐term memory (LSTM) or its variants have been widely used in recent studies, they may produce unacceptable results in long‐term prediction due to the iterative output that accumulates error. To address this issue, a transformer‐based long‐term trajectory prediction model is proposed here, which utilizes the self‐attention mechanism to extract time series features from historical trajectory data. For long‐term prediction scenarios, we a trajectory stabilization module is introduced to ensure the stationarity of the time series for better predictability. Additionally, the transformer output strategy is improved to generate the prediction sequence by a single step instead of serial dynamic decoding, thus effectively enhancing the precision and inference speed. The proposed model is validated using real data obtained from China's Southwest Air Traffic Management Bureau. The experimental results demonstrate that this model outperforms the benchmark model. Further ablation experiments and visualizations are performed to analyze the impact of trajectory stabilization and one‐step inference strategy.

Association rule mining of aircraft event causes based on the Apriori algorithm

To reveal complex causes of aircraft events, this paper aims to mine association rules between the trigger probability and relative strength via a modified Apriori algorithm. Clustering is adopted for data preprocessing and TF–IDF value calculation. Causative item sets of aircraft events are obtained based on the accident causation 2–4 model and are coded to establish code indicators. By avoiding the use of statistical methodologies to resolve not-a-number (NaN) values for altering the interrelations among causes, an enhancement in the Apriori algorithm is proposed by considering frequent items. By extracting frequent patterns, in this paper, all the association rules that satisfy three perspectives (support, confidence and lift) are determined by constantly generating and pruning candidate item sets. A network graph is used to visualize the association rules between different unsafe events and all types of causes. Finally, 9835 representative pieces of data, including general unsafe events, general incidents and serious incidents from the Southwest Air Traffic Management Bureau, are selected for analysis. The results show that improper energy allocation, poor conflict resolution ability, inadequate onsite management duties, adoption of a luck mentality, and occurrence of controller oversight are highly correlated with general unsafe events, and failure to rectify incorrect recitation is notably correlated with general incidents, while inadequate manual promotion, lack of conflict judgement and insufficient safety management are strongly correlated with serious incidents. This study quantitatively reveals the potential patterns and characteristics of mutual interactions among various types of historical aircraft events and highlights directions for controllable prevention and prediction of aircraft events.

Accuracy, accessibility, and institutional capacity shape the utility of habitat models for managing and conserving rare plants on western public lands

AbstractPublic lands are often managed for multiple uses ranging from energy development to rare plant conservation. Habitat models can help land managers assess and mitigate potential effects of projects on rare plants, but it is unclear how models are currently being used. Our goal was to better understand how staff in the Bureau of Land Management currently use habitat models to inform their decisions, and perceived challenges and benefits associated with that use. We first examined litigation documents to determine whether the agency has been challenged on its use of data for rare plants and found no relevant legal challenges. Second, we analyzed model use in National Environmental Policy Act (NEPA) documents and found no clear citations of habitat models. Finally, we conducted interviews with agency staff who analyze potential effects of proposed actions on rare plants in NEPA documents. The primary challenges interviewees faced in using models related to data organization and access, model quality and accuracy, and institutional capacity. Interviewees believed models could be used more to inform decisions and actions to conserve rare plants and rare plant habitat on public lands and recommended improving staff access to models, creating models for additional species, and addressing staffing limitations.

COMPARATIVE ANALYSIS OF LOW-COST CONSUMER-GRADE AND COMMERCIAL-GRADE DRONES FOR LAND SURVEYING APPLICATIONS

Abstract. This study investigates the feasibility of using low-cost consumer drones, specifically the DJI Mini 2, for land surveys compared to commercial-grade drones like the DJI Phantom 4 Pro V2. The research, conducted within the University of the Philippines - Diliman campus, evaluates the horizontal accuracy of resulting ortho-images and explores the advantages and disadvantages of each platform. Initiated by the recognition of aerial drones' transformative impact on land surveying, particularly acknowledged by the Land Management Bureau in the Philippines, the study addresses concerns about the use of consumer-grade drones for surveying. While some advocate for commercial-grade drones, citing concerns about accuracy, a prior study in India demonstrated the suitability of consumer-grade drones for geomatics applications. The methodology involves creating a flight plan with specified parameters for both drones, establishing Ground Control Points (GCPs), and conducting two flights. The results, processed using UAS Mapping Workflow, indicate comparable errors between the consumer-grade DJI Mini 2 and commercial-grade DJI Phantom 4 Pro V2. Despite slight differences, both drones meet the accuracy standards for land surveys. The study contributes to the discourse on affordable means of secure land tenure, envisioning consumer-grade drones as viable alternatives for cost-effective land surveys. The DJI Mini 2, at a fraction of the cost, demonstrates the capability to achieve accuracy levels comparable to its commercial counterpart. While acknowledging the need for further testing and optimization, the findings suggest the potential of consumer-grade drones in advancing sustainable urban development and poverty reduction through accessible land survey methods.

SIMULATING THE EFFECTS OF EURO 4 DIESEL-POWERED ENGINE JEEPNEYS ON AIR QUALITY AND UNDERSTANDING ESTIMATED HEALTH RISK TOWARDS SUSTAINABLE TRANSPORTATION

Abstract. The Euro-4 diesel-powered engines are the current industry standard in the Philippines as indicated in the Public Utility Vehicle Modernization Program (PUVMP) Omnibus Guidelines Department Order 2017-011. Based on the National Emissions Inventory report of the Environmental Management Bureau in 2018, 74% of air pollutant concentrations were produced by mobile sources including jeepneys. The PUVMP is focused on enhancing environmental sustainability, air quality, and in providing a reliable and effective public transportation system. The potential advantages to air quality and health from the full implementation of the program especially the Euro 4 diesel-powered engine jeepneys in Trece Martires City are assessed in this paper. The study aims to estimate the impact of the possible enforcement of Euro 4 diesel-powered engine jeepneys on the reduction of air pollution in the research locale. Four pollutants were assessed particularly Carbon Monoxide (CO), Nitrogen Oxide (NOx), Sulfur Oxide (SOx) and Particulate Matter 2.5 (PM2.5) using AERMOD Air Dispersion Modeling Software in five (5) different scenarios: (1) baseline engine jeepneys, (2) 25% implementation of Euro 4 diesel-powered engine jeepneys, (3) 50% implementation of Euro 4 diesel-powered engine jeepney, (4) 75% implementation of Euro 4 diesel-powered engine jeepneys and (5) full implementation of Euro 4 diesel-powered engine jeepneys. AirQ+ was utilized to evaluate the health risk of Euro 4 diesel-powered engine jeepneys to the drivers and commuters in the vicinity. Result shows that the Scenario 5 or the full implementation of Euro 4 diesel-powered engines relatively reduces CO by 84.30% (8.355 μg/cu.m to 1.31 μg/cu.m), NOx by 21.76% (10.6 μg/cu.m to 8.27 μg/cu.m), and PM2.5 by 83.36% (2.69 μg/cu.m to 0.447 μg/cu.m), by its maximum estimated concentrations. However, an increase by 14.14% of SOx emissions (0.091 μg/cu.m to 0.104 μg/cu.m) were seen on the simulation from Scenario 1 to Scenario 5. In terms of health risk assessment, higher levels of PM2.5 exposure exhibit an increase in health hazard with respect to mortality rate. Simulation outputs indicate that transitioning of jeepneys from current technology to Euro 4 models reduces pollution levels and lowers health risk, hence, can be used as basis in enhancing transport plans and health monitoring strategies in the city.

Water Quality Assessment of Mananga River Using Principal Component Analysis

The Mananga River in the Philippines has been classified as a Class A river in 1997. Since then, the river has significantly deteriorated due to pollution, especially in the downstream area around Talisay in the Cebu region. In this study, the water quality parameters – namely, dissolved oxygen (DO), biological oxygen demand (BOD), and total suspended solids (TSS) – were assessed using principal component analysis (PCA). Water quality data were obtained from the Department of Environmental and Natural Resources–Environmental Management Bureau Region 7. The water samples were collected on a quarterly basis from 2016–2019. The effect of weather conditions on water quality and significant relationships between the water quality parameters were determined. In addition, the comparison of water quality in each sampling station was investigated. Results show that about 84.3% of the total variance in water quality can be attributed to two significant principal component scores. Evident correlations were observed such as DO and BOD are negatively correlated, whereas a positive correlation exists between DO to RH and wind speed, BOD to temperature, and TSS to wind speed. Furthermore, negative correlations are observed between DO to temperature and wind direction, BOD to rainfall, and TSS to wind direction and rainfall. In the overall analysis of the results, the heavier the influence of a variable, the more likely it is to contribute to affecting the water quality. Therefore, this can alter the overall distribution within the plots and the correlations among the variables. The findings are a predictive measure of future changes and trends in the Mananga River. Therefore, the results of the present work will be used in environmental monitoring, environmental management, and assistance for the rehabilitation of the Mananga River using PCA.

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

Satellite NO2 Trends and Hotspots Over Offshore Oil and Gas Operations in the Gulf of Mexico

AbstractThe Outer Continental Shelf of the Gulf of Mexico (GOM) is populated with numerous oil and natural gas (ONG) platforms which produce NOx (NOx = NO + NO2), a major component of air pollution. The Bureau of Ocean Energy Management (BOEM) is mandated to ensure that the air quality of coastal states is not degraded by these emissions. As part of a NASA‐BOEM collaboration, we conducted a satellite data‐based analysis of nitrogen dioxide (NO2) patterns and trends in the GOM. Data from the OMI and TROPOMI sensors were used to obtain 18+ year records of tropospheric column (TrC) NO2 in three GOM regions: (a) Houston urban area, (b) near shore area off the Louisiana coast, and a (c) deepwater area off the Louisiana coast. The 2004–2022 time series show a decreasing trend for the urban (−0.027 DU/decade) and near shore (−0.0022 DU/decade) areas, and an increasing trend (0.0019 DU/decade) for the deepwater area. MERRA‐2 wind and TROPOMI NO2 data were used to reveal several NO2 hotspots (up to 25% above background values) under calm wind conditions near individual platforms. The NO2 signals from these deepwater platforms and the high density of shallow water platforms closer to shore were confirmed by TrC NO2 anomalies of up to 10%, taking into account the monthly TrC NO2 climatology over the GOM. The results presented in this study establish a baseline for future estimates of emissions from the ONG hotspots and provide a methodology for analyzing NO2 measurements from the new geostationary TEMPO instrument.

Effects from particle motion and substrate-borne vibration on fishes and invertebrates: Recommendations on research questions and methodologies

There have been substantially increased interest in effects of particle motion and substrate-borne vibration on fishes and aquatic invertebrates over the past decade. This is because these signals, unlike sound pressure, are the basis of hearing in most fishes and in all aquatic invertebrates. However, studies to address these issues continue to face challenges due to the diversity of species, the broad range of hearing mechanism, and the complexity of the physical acoustic environment in conducting studies. Additionally, we do not yet have a good understanding of, and mechanisms for, source generation, calibration, and measurements to be able to examine effects properly. Related to this is the critical issue is how research questions are applicable to regulatory agencies. In October 2023, the US Bureau of Ocean Energy Management held a workshop to address different research methodologies and their pros and cons as the basis for study of the behavioral and physiological responses to particle motion and substrate-borne vibration. Subsequently, a review was conducted linking research priorities previously identified concerning anthropogenic noise effects on animals with appropriate research methodologies. The review also provides recommendations on experimental settings that are most appropriate to address specific research questions for regulatory concerns.