Article updated on 26 November 2021
Coastal ecosystems undergo pressures from both offshore and land-based human activity along with human wastewater—an area that is less researched. The current methods used for the same do not account for both nitrogen (N) and pathogen inputs. Looking at Tuholske, C. et al's paper published in the journal PLOS ONE, this article discusses the use of a new high-resolution geospatial model to evaluate and map N and pathogen from human sewage for ~135,000 watersheds around the world.
Image Credit: Davdeka/Shutterstock.com
Coastal marine ecosystems undergo various pressures, including overfishing, climate change, offshore commercial uses, and land-based activities such as agriculture. Nutrient and chemical pollution run-off from land-based activities connect coastal marine systems to terrestrial human activities.
It has been noted that agricultural fertilizers and livestock waste play a major role in coastal eutrophication, hypoxic zones, harmful algal blooms, or anoxic dead zones with significant impacts which are worsened with global climate change.
Certain studies measured and mapped the effects of human sewage on coastal ecosystems which are known to contribute significantly to anthropogenic N inputs. However, treatment methods involved emitting N while removing pathogens, and there is no combined research on nutrient input and pathogen risk as of now.
Present processes analyzing nitrogen or pathogen input to surface water from human sewage have their own set of limitations as they both rely on a common modeling design and do not account for the impact of future climate and socioeconomic change.
This study is the first of its kind presenting a globally comprehensive, fine-resolution (~1-km) analysis of N and pathogen from wastewater from almost 135,000 watersheds and coastal zones that drain into the ocean.
The study evaluates differences between N and pathogen inputs and the estimated potential exposure of two major sensitive habitats (coral reefs and seagrass beds) to these inputs.
AZoCleantech spoke to Cascade Tuholske, the Earth Institute Postdoctoral Research Scientist from Columbia University working on the project:
Our study literally puts the problem of wastewater inputs to the ocean on the map. Until now, we have lacked a high resolution understanding of how wastewater impacts coastal ecosystems worldwide. But by mapping both Nitrogen and pathogen wastewater inputs across 133,000 plus watersheds, we can begin to address the problem and improve both human and ecosystem health across coastal waters worldwide.
Cascade Tuholske, Earth Institute Postdoctoral Research Scientist, Center for International Earth Science Information Network (CIESIN), Columbia Climate School, Columbia University
Both nitrogen effluent (N, grams yr−1) and pathogens [as estimated by fecal indicator organisms (FIO)] were created through a similar approach. The population and settlement type data (~1 km resolution) were merged with national-level statistics on protein consumption (for nitrogen alone).
The study used the following programs to carry out the analyses:
- Python v3.7
- R v3.6.3
- GRASS GIS v7.8.3
European Global Human Settlement Population Layer version 4 (GHS-Pop) was employed to provide population estimates for 2015. GHS-Pop is the sole gridded population dataset with corresponding settlement typologies (GHS-SMOD) created from a common modeling paradigm.
National statistics from WHO-UNICEF 2017 Joint Monitoring Project Wastewater (JMP) was used to estimate the amount of N removed from wastewater and access to sanitation was employed to calculate N production coefficients.
Three sewage treatment categories of nitrogen removal efficiency were developed. The proposed model utilized a uniform N removal rate for sewage systems. FIO production was modeled as a function of sanitation infrastructure and population size. This enables evaluating the exposure of coastal ecosystems to FIOs.
The model presumed that populations with inputs from septic tanks or open defecation more than a kilometer far from coastlines and surface water do not contribute to effluent totals.
To evaluate pixel-level N effluents, the proposed model utilized FAO’s Food Balance Sheets containing information for 178 countries to look at annual national estimates for grams of protein consumed per capita.
As metabolic research has established that 16% of the protein ingested is excreted in various forms of N, the pixel-level consumption was scaled by 0.16 to obtain an N excretion base. A database of national-level protein consumption and per capita GDP was constructed to account for the unavailable data.
A high-resolution watershed vector data with corresponding pourpoints were developed with an automated flow-accumulation process. To estimate each nation’s discharge into the world’s oceans, the effluents of all the pourpoints within the country were summed.
The plume model helped to distribute values into coastal waters based on a cost path. This enables drivers to wrap around headlands and islands.
The modeled wastewater plume data evaluated coal and seagrass exposure to N inputs from wastewater. The N values for each sanitation system and the total N from all wastewater for each raster cell containing the habitat were extracted.
The proposed model shows that wastewater inputs into coastal waters amount to an estimated 6.2 Tg N of total anthropogenic N in coastal ecosystems around the world. The current fine-resolution model enables the identification of locations of specifically high (or low) inputs (see Figure 1).
Figure 1. Global distribution of total wastewater N. (A) Global map of the terrestrial sources (green to blue) and coastal diffusion of inputs (yellow to purple) of total wastewater N, measured in log10(gN) in both. Coastal plumes have been buffered to line segments to exaggerate patterns to be visible at the global scale. Insets show zoomed-in views of the (B) Ganges, (C) Danube, and (D) Chang Jiang (Yangtze) Rivers, showing wastewater plumes at high resolution. Image Credit: Tuholske, et al., 2021.
Figure 2 underlines the significant variation by country and region.
Figure 2. Total nitrogen input into Exclusive Economic Zone (EEZ) waters of coastal countries, by source type (sewer, septic, direct). The global total wastewater input is 6.2 Tg N, with 3.9 Tg from sewers, 0.3 Tg from septic, and 2 Tg from direct input. The top 40 countries are shown in the horizontal bar chart; the remaining countries are in the pinwheel, grouped by continent or larger geographical region. Note that the Netherlands is shown in both places (in red) to help connect the scale of the two parts of the figure. Image Credit: Tuholske, et al., 2021.
The proposed model indicates that wastewater input of N from watersheds into coastal waters is highly concentrated, with half (n = 67,308) of all watersheds adding no nitrogen or pathogens.
The wastewater N source differs across the watersheds—from sewered to direct input. By modeling the plume of wastewater N into coastal waters, it was evaluated that around 58% of all coral reefs worldwide and 88% of all seagrass beds encounter some anthropogenic N input from wastewater (see Figure 3).
Figure 3. Expected impact of N on sensitive coastal habitats. Maps show where (A) coral reefs and (B) seagrass beds are heavily impacted (raster cells in top 2.5% of exposure; red dots), not impacted (no exposure to wastewater N; dark blue dots), or impacted but not in the top 2.5% (yellow dots). Raster cells are represented as points that visually over-represents the habitat; red is overlaid on top which makes it visually dominant; blue points are transparent and overlaid on green/yellow points such that higher densities of unimpacted areas are brighter blue. Image Credit: Tuholske, et al., 2021.
Along with wastewater impacts, pressure from overfishing and habitat degradation from coastal development add to the other stressors.
Wastewater contains human pathogens and excess N, posing a risk to both human health and ecological health. The study found that 25 watersheds contributed to over 51% of FIO into the ocean.
Wastewater impacts human health by creating elevated levels of pathogens that make us sick. At the same time, Nitrogen from wastewater impacts coastal ecosystems, creating harmful algal blooms that can lead to coastal dead zones. Coastal ecosystems are fragile. We are worried that too much Nitrogen in coastal areas can lead to tipping points where marine life cannot recover.
Cascade Tuholske, Earth Institute Postdoctoral Research Scientist, Center for International Earth Science Information Network (CIESIN), Columbia Climate School, Columbia University
Figure 4. The relationship between watershed level input of N versus FIO. Watersheds for which total N exceeds (yellow to red colors) or is well below (green to blue colors) expected levels given predicted nitrogen/pathogen outputs from their correlation. Global map (A) and scatterplots of all watersheds, both full extent (B) and zoomed in (C). Watersheds for which the levels are proportional to expectations are white on the map, inclusive of the nearly 50% of (very small) watersheds for which there are no nitrogen or pathogen inputs. Dots in the scatter plot are scaled to the size of the watershed. Image Credit: Tuholske, et al., 2021.
Figure 4 shows spatial heterogeneity when comparing N vs. FIO input.
Places where N and FIO inputs are highly correlated pose a significant challenge in discovering a comprehensive solution.
This article provides crucial information required to give the needed clarity, highlighting FIO and N inputs across all watersheds, and also by country. However, the proposed model does not completely account for variations in land cover, sanitation efficiency, ecosystem processes, and other biogeochemical processes. The study also did not account for the input of phosphorus or other chemicals and pollutants that harms habitats and species.
This study is the first to produce fine-resolution, comparable data mapping land-based sources and downstream exposure of both pathogens and N in coastal ecosystems and employs sophisticated, high-resolution data on urbanization and population size.
The model offers a contrast between high spatial resolution demographic drivers and coarse-grained landscape dynamics. This model can be used to pinpoint priority hotspots for in-depth in situ monitoring that can identify the true sources and quantities of pollutants such as N.
Tuholske, C., Halpern, B. S., Blasco, G., Villasenor, J. C., Frazier, M., Caylor, K. (2021) Mapping global inputs and impacts from of human sewage in coastal ecosystems. PLOS ONE, 16(11), p. e0258898. Available at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0258898.
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