Kajian Kualitas Air Berdasarkan Keanekaragaman Meiofauna dan Parameter Fisika-Kimia di Pesisir Losari, Makassar

Pesisir merupakan kawasan yang rentan mengalami penurunan kualitas perairan akibat masuknya bahan-bahan pencemar hasil aktivitas antropogenik dari daratan. Penelitian ini bertujuan untuk untuk mengkaji kualitas perairan berdasarkan keanekaragaman meiofauna dan parameter fisika-kimia di pesisir Losari, Makassar. Selain itu penelitian ini dilakukan untuk menganalisis pengaruh parameter fisika-kimia terhadap keanekaragaman meiofauna di dasar perairan. Penelitian ini bersifat kuantitatif dengan teknik pengambilan data secara purposive sampling. Status kualitas perairan di pesisir Losari dikategorikan sebagai perairan yang tercemar berat, hal ini didasarkan pada tingkat keanekaragaman spesies meiofauna yang sangat rendah dan sebagian besar parameter fisika-kimia perairan yang tidak memenuhi baku mutu yang telah ditentukan oleh pemerintah RI melalui Kep. MLH. No. 51 Tahun 2004. Kecerahan, DO, Suhu, kedalaman, salinitas, dan nitrat sedimen merupakan parameter fisika-kimia yang berkorelasi positif atau berpengaruh terhadap tingkat keanekaragaman meiofauna. Adapun parameter lingkungan perairan yang berkorelasi negatif terhadap tingkat keanekaragaman meiofauna di pesisir Losari, diartikan sebagai hubungan yang tidak menguntungkan. Kondisi ini terjadi akibat meiofauna merasa terganggu atas sebaran fosfat sedimen, nitrat air laut, fosfat air laut, dan pH yang tidak memenuhi baku mutu air laut.ABSTRACTThe Coastal zone are susceptible to decreasing water quality due entry of pollutants from anthropogenic activities in the mainland. This study assessed water quality based on meiofauna diversity and physical-chemical parameters in the Losari coast, Makassar. Furthermore, this study was to analyze the physical-chemical parameters effect on the diversity of meiofauna at the seabed. It employed a quantitative approach with purposive sampling technique. Water quality status on the Losari coast categorized as heavily polluted waters, this based on low level of meiofauna species diversity and most of the physical-chemical parameters does not meet the quality standards determined by Indonesian government through Kep. MLH. No. 51 of 2004. Brightness, DO, temperature, depth, salinity, and sediment nitrate are physical-chemical parameters positively correlated or influenced of meiofauna diversity level. The aquatic environmental parameters negatively correlated with meiofauna diversity level in the Losari coast are interpreted as an unfavorable relationship. This condition occurs because the meiofauna feel disturbed by distribution of sedimentary phosphate, seawater nitrate, seawater phosphate, and pH that does not meet seawater quality regulations.

Study on Total Control of Total Nitrogen in the Laizhou Bay

Human activity imposes a stronger and increasing impact on the coastal environment by land-based discharge and run-off pollution inputs. Land-based total nitrogen (TN) pollution, as the main cause of eutrophication in the Laizhou Bay, China, should be controlled effectively. Based on a three-dimensional pollution transport model, 20 groups of allocation schemes were designed under the requirement that the allocations of three estuaries in the inner bay were adjusted properly, while the two estuaries in the outer bay, i.e., the Yellow River and the Jiehe River, were kept unchanged. The statistical results show that the area ratio of heavily polluted seawater to the entire Laizhou Bay reached the maximum (35.14%) when the load allocation of the Xiaoqinghe River accounted for a high proportion (65%), and the Yuhe River and the Jiaolaihe River accounted for 15% and 20%, respectively. Overall, the pollution levels of the Laizhou Bay were positively associated with the allocation of the Xiaoqinghe River. Reducing pollutant allocation in the Xiaoqinghe River contributed most to the improvement of the seawater quality of the entire Laizhou Bay, and it was followed by a reduction in the Yuhe River and the Jiaolaihe River.

Long-Term Temporal and Spatial Distribution of Coliform Bacteria in Jiaozhou Bay Associated With Human Activities and Environmental Governance

Coliform bacteria (CB) can be used as an indicator of seawater quality. Long-term monitoring of seawater quality based on CB abundance is lacking in Jiaozhou Bay. In this study, CB abundance in surface seawater of 12 different stations in Jiaozhou Bay was investigated by culturing method. The results showed that: (1) the abundance of CB showed a decreasing tendency during the investigation. During 2004–2007, 2008–2013, and 2014–2017, the average CB abundance decreased significantly, forming a “three stages phenomenon”; (2) the average CB abundance in the first half of the year was lower than that in the second half; (3) the CB abundance in Jiaozhou Bay was spatially heterogeneous. The maximum average CB abundance was observed in the estuary area, and followed by the bay mouth area, the outer bay area, and the inner bay area. The highest abundance may be associated with sewage discharge related to human activities; (4) the abundance of CB was most positively correlated with the concentration of ammonium salt and nitrate, while most negatively correlated with salinity; (5) the years 2007 (2008) and 2013 (2014) were time points of the “three stages phenomenon.” These time points coincide with environmental governance actions, indicating that the actions have played a prominent role in improving seawater quality. Long-term survey of CB can not only serve as an indicator of seawater quality, but also provide a basis for the development of environmental governance strategies and pollution control.

Springs® Design Optimized By Seawater Quality. Laboratory Pilot Tests

A new seawater laboratory pilot has been installed in order to evaluate the impact of the seawater quality on the performance of nanofiltration membranes and filters. The test program implemented was designed to produce the data required to optimize the design and operating parameters of a subsea sulfate removal plant, particularly with respect to the technology developed by Total, Saipem and Veolia, co-owners of the development. The equipment qualification plan is approaching completion with the development of subsea barrier-fluidless pumps, all-electric control systems, high-cycling valves operated by electric actuators and subsea water analyzers. This presented pilot laboratory study completes this plan. Nanofiltration membranes are commonly used to remove the sulfates found in seawater before the water is injected into wells. The principal advantages of relocating this equipment from topside to subsea are better reservoir sweep control, a substantial subsea water injection network reduction and savings on space and weight on the topsides deck. The move to subsea offers the opportunity to simplify the process due to improved deep water quality. This was previously demonstrated through a subsea test campaign. This new pilot study provides data both on the performance of a plant operating with different feed water quality and on the success of operating changes to further optimize the plant performance. The pilot has been installed at the Palavas-les-Flots site in France. Raw water collected from the basin was mixed with ultra-filtered water in order to calibrate the feed water quality. The pilot includes a two stage nanofiltration configuration and single stage nanofiltration unit. The two stage configuration was used to produce data for operation across an array of feed water quality and plant operating conditions. The single stage unit was used to produce data on membrane fouling over a long operating duration. Results from these tests and discussion on how this data relates to subsea plant performance shall be presented. This innovative approach enables a wide range of subsea water quality to be simulated and tested against different process configurations of the subsea unit. Indeed, for each industrial subsea application, the raw seawater quality is dependent on both the region and the depth of the seawater inlet. With this experimental data acquisition campaign and understanding of the seawater quality at inlet, the system design can be tailor-made for each future application case.

Remote sensing inversion of water quality in coastal sea area based on machine learning: a case study of Shenzhen bay, China

<p>Remote sensing monitoring has the characteristics of wide monitoring range, celerity, low cost for long-term dynamic monitoring of water environment. With the flourish of artificial intelligence, machine learning has enabled remote sensing inversion of seawater quality to achieve higher prediction accuracy. However, due to the physicochemical property of the water quality parameters, the performance of algorithms differs a lot. In order to improve the predictive accuracy of seawater quality parameters, we proposed a technical framework to identify the optimal machine learning algorithms using Sentinel-2 satellite and in-situ seawater sample data. In the study, we select three algorithms, i.e. support vector regression (SVR), XGBoost and deep learning (DL), and four seawater quality parameters, i.e. dissolved oxygen (DO), total dissolved solids (TDS), turbidity(TUR) and chlorophyll-a (Chla). The results show that SVR is a more precise algorithm to inverse DO (R<sup>2</sup> = 0.81). XGBoost has the best accuracy for Chla and Tur inversion (R<sup>2</sup> = 0.75 and 0.78 respectively) while DL performs better in TDS (R<sup>2</sup> =0.789). Overall, this research provides a theoretical support for high precision remote sensing inversion of offshore seawater quality parameters based on machine learning.</p>