Microplastics (MPs) in the ocean have been widely recognized as causing global marine environmental problems. To gain a quantitative and comprehensive understanding of oceanic MP contamination, detailed numerical Lagrangian particle tracking experiments were conducted to evaluate the regional oceanic transport and dispersal of MPs in the South China Sea (SCS) derived from three major rivers, Pearl (China), Mekong (Vietnam), and Pasig (the Philippines), which are known to discharge large amounts of plastic waste into the SCS. As previous field surveys have suggested, MP contamination spreads from the surface to the deeper ocean in the water column, we thus considered three types of MPs: (1) positively buoyant (light) MPs, (2) positively buoyant (light) MPs with random walk diffusion, and (3) full 3-D tracking of non-buoyant MPs that are passively transported by ambient currents. Transport patterns of these MPs from the three rivers clearly showed the intra-annual variability associated with seasonally varying circulations driven by the Asian monsoons in the SCS. Many MPs floating during the prevailing southwest monsoon are transported to the northwest Pacific Ocean and the East China Sea through the Luzon Strait and the Taiwan Strait to form MP hotspots. Non-buoyant MPs are broadly transported from the surface layer to depths of approximately 100 m or deeper, where in situ observations are rare. In addition, the buoyant MPs drifting on the continental shelf originating from southern China tend to be pushed toward the shore and beached by northward wind-induced currents more pronouncedly than the non-buoyant MPs. Therefore, the river-derived MPs to the SCS were found to serve as sources to adjacent basins and oceans, to be distributed not only in the upper layer but also in the abyssal ocean (non-buoyant MPs), and to be transported to the shores (buoyant MPs).

The emergence of the COVID-19 pandemic has caused worldwide health constraints. This study was conducted to establish a baseline monitoring survey to describe the distribution of PPE litters during the COVID-19 pandemic in the province of Palawan, Philippines. A total of 386 COVID-19-related PPE items were present in 83 % of coastal sampling sites with over a cumulative area of 48,200 m², with a density of 8 × 10⁻³ items m⁻². The facemask (98 %; n = 377) was the primary type of PPE, followed by face shield (2 %; n = 9). Meanwhile, the daily density of PPE litters in San Manuel, Puerto Princesa ranged from 0 to 9.9 × 10⁻² items m⁻², with a mean density of 8 × 10⁻³ items m⁻². The accumulation rates of PPE items ranged from 3.27 × 10⁻¹ items to 1.143 items d⁻¹, with an average rate of 7.29 × 10⁻¹ items d⁻¹.

This empirical study examines the factors enhancing environmental governance for marine plastic litter abatement in Manila, the Philippines. We use a combined covariance-based hybrid structural equation modeling (SEM) and DPSIR framework, with data collected via an online survey from 456 barangays in Manila, the Philippines. The survey was processed and analyzed using a combined model, validated through interviews and focused group discussions. With Higher-Order Model good internal consistency (0.917) and achieved measures of CFI (0.992), RMSEA (0.036), and SRMR (0.019), the findings revealed that environmental governance (COVID-19 waste), community participation, socio-economic factors, and solution measures have positively affected marine plastic litter (MPL) abatement. Notwithstanding, environmental governance (SWM policies and guidelines) has a negative impact on MPL abatement. There is, however, no link between waste infrastructure and MPL abatement. The findings provide significant perspectives in Manila to enhance environmental governance for MPL abatement. This paper presents policy-actions implications drawn from DPSIR-SEM.

The study examined the dynamic nexus between carbon footprints, nonrenewable energy and renewable energy consumption, financial development and economic growth, and combating climate change by using a dataset of selected 13 Asian emerging economies (Bangladesh, China, India, Indonesia, Iran, Malaysia, Nepal, Pakistan, Philippines, South Korea, Sri Lanka, Thailand, and Vietnam) from 1995 to 2020. This study empirical analysis uses the second generation of panel cointegration techniques to compensate for cross-sectional dependency and slope heterogeneity. The mean group, the common correlated effects mean group, and the augmented mean group are used to estimate the long-run equations. The findings suggest that economic growth and nonrenewable energy consumption exacerbate environmental degradation, but renewable energy consumption mitigates the total adverse effects on the environment over time. Additionally, economy-specific findings examine how the impact of nonrenewable energy and renewable energy consumption on the carbon footprint depends on energy consumption level. Furthermore, the Dumitrescu-Hurlin causality test reveals a statistically significant bidirectional correlation between financial development, carbon footprints, economic growth, and consumption of nonrenewable energy and renewable energy. Finally, the study says that Asian emerging economies should use more renewable energy and be more efficient in order to reduce their carbon footprints.

This research aims to investigate the effect of foreign direct investment on carbon emissions through the panel ARDL method using annual data for the 1990–2016 period for the newly industrialized countries (NICs), including China, Malaysia, Mexico, Philippines, Thailand, Turkey, India, and Brazil. The stationarity of the series was obtained through LLC, IPS, and Fisher ADF panel unit root tests, the cointegration relationship with the panel ARDL-PMG approach, and the causality relationship with Dumitrescu and Hurlin (DH) tests. As a result of the long-term analysis, the foreign direct investment, energy consumption, and trade openness have a positive and significant impact on carbon emissions, whereas economic growth has a negative and significant impact on carbon emissions. The result shows that a percent increase in foreign direct investment increases carbon emissions by 0.03%. As a result of the short-term analysis, it was seen that the coefficient of the error correction term (ECT) was negative and statistically significant. According to DH panel causality test results, there exists a bidirectional causality relationship among energy consumption and carbon emissions, and a unidirectional causality relationship from economic growth and trade openness to carbon emissions and from carbon emissions to foreign direct investment. As policy implication, in industrialized countries especially China and India, there is a greater need to invest in green energy consumption at a larger scale to achieve future sustainable development goals.

Consumption advice to ensure the health and safety of fish consumers remains urgent to handle the ever-increasing panic over heavy metal toxicity. Moreover, studies of fish consumption rarely focus on the perceptions and awareness of consumers. Considering this, the present study examines the factors determining the willingness to follow fish consumption advice as well as calculate the risk–benefit ratio and produce the vulnerability map followed by formulating fish consumption advice for consumers of two commercially important fish species, tilapia (Oreochromis niloticus) and mudfish (Ophiocephalus striatus), in the Laguna de Bay area of the Philippines. Primary data on consumers’ perceptions were collected through a questionnaire, whereas heavy metal contamination data were compiled from the best available literature. We concluded that people’s willingness to adopt consumption advice is mostly dependent on their existing level of fish consumption (P = 0.000). There was no discernible difference in the mean concentration of heavy metals in fish between the dry and wet seasons, with the exception of As concentrations in the samples (t15.75 = 3.72, p < 0.001). The hazard quotient (risk–benefit ratio) for fish consumption (HQefa) was an order of magnitude higher in the mudfish samples (0.05 and 28.28) compared to tilapia (0.04 to 16.02). Binangonan and Taguig from the Northern West Bay (1A, 1B) were clearly recognised on the vulnerability map as the most vulnerable regions in the lake. In general, it was determined that As and Pb were the elements causing consumption restrictions on tilapia collected from various parts of Laguna Lake. As with tilapia, locations with a high-risk advisory for mudfish were identified as the Northern West Bay and Central Bay, with a consumption limit of five meals per month due to excessive mercury pollution. This empirical study can serve as an option for the future development of fish consumption advice in the region.

This study is hinged on analyzing factors such as agriculture and globalization (de jure trade and financial) that threaten a sustainable environment using two proxies of ecological footprint: carbon and noncarbon ecological footprint in the Philippines while controlling for the influence of fossil to GDP, economic growth, urban population, and financial development using the autoregressive distributed lag (ARDL) framework. The result provides evidence of long‐run stable state among the variables. The result validates inverted U‐shaped pattern of EKC involving relationship between agricultural development and ecological footprint for the Philippines indicating that initially, ecological footprint increases as the agriculture develops and then declines as the agriculture matures to generate efficiency and low carbon. In addition, this study explores elasticities of the variables using ARDL, FMOLS, DOLS, and CCR procedure and found that de jure financial globalization exerts positive influence on ecological footprint in the long run. De jure trade globalization is found to be negative and significant in the long run. It is also found that agricultural level operates below the threshold level required to maximize the growth benefits of agricultural system towards mitigating environmental sustainability. Further empirical result shows a positive relationship between economic growth, fossil fuel, urban-population growth, and ecological footprint, and negative insignificant relationship between credit to private sector and ecological footprint. The government should optimize the use of agricultural land through well-articulated economic integration strategy fashioned to pave way for cleaner and low-carbon technologies sources like solar, geothermal, biomass, biogas, tidal power, photovoltaic, and wind energy in the agricultural production to avoid further deterioration of the environment.

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.