4 research outputs found
Sources and Pathways of Nutrients in the Semi-Arid Region of BeijingâTianjin, China
Semiarid regions worldwide are particularly prone to eutrophication,
which causes immense ecological and economic problems. One region
that is in transition and requires systematic research for effective
intervention is the dry landscape of Beijing-Tianjin (P. R. China).
We investigated the sources and spatiotemporal loads of nitrogen and
phosphorus species over a one-year period in the Haihe catchment that
drains the megacity of Beijing. Although wastewater treatment was
improved in recent years, the rivers were heavily contaminated by
0.3â5.3 mgP L<sup>â1</sup> and 3.0â49 mgN L<sup>â1</sup>, with toxic levels of nitrite (â„1 mgNO<sub>2</sub>âN L<sup>â1</sup>) and ammonia (â„0.6
mgNH<sub>3</sub>âN L<sup>â1</sup>). The average NH<sub>4</sub><sup>+</sup> (16.9 mgN L<sup>â1</sup>) increased by
160% compared to 1996-levels. Mass fluxes and ÎŽ<sup>15</sup>N-signatures revealed that nutrients originated almost exclusively
from sewage. Furthermore, the water balance demonstrated that >90%
of the polluted river water was diverted for irrigation, thereby threatening
food safety and groundwater quality. Per capita loads of 1.42 kgN/yr
and 115 gP/yr were comparable to the peak discharges typical of Europe
and the United States in 1970â1990, but concentrations were
2â3 times higher in the BeijingâTianjin region. Our
research identified sewage as the predominant nutrient source in this
semiarid region, which suggests that state-of-the-art wastewater treatment
would drastically mitigate eutrophication and even more rapidly than
was previously observed in Europe
Sources and Pathways of Nutrients in the Semi-Arid Region of BeijingâTianjin, China
Semiarid regions worldwide are particularly prone to eutrophication,
which causes immense ecological and economic problems. One region
that is in transition and requires systematic research for effective
intervention is the dry landscape of Beijing-Tianjin (P. R. China).
We investigated the sources and spatiotemporal loads of nitrogen and
phosphorus species over a one-year period in the Haihe catchment that
drains the megacity of Beijing. Although wastewater treatment was
improved in recent years, the rivers were heavily contaminated by
0.3â5.3 mgP L<sup>â1</sup> and 3.0â49 mgN L<sup>â1</sup>, with toxic levels of nitrite (â„1 mgNO<sub>2</sub>âN L<sup>â1</sup>) and ammonia (â„0.6
mgNH<sub>3</sub>âN L<sup>â1</sup>). The average NH<sub>4</sub><sup>+</sup> (16.9 mgN L<sup>â1</sup>) increased by
160% compared to 1996-levels. Mass fluxes and ÎŽ<sup>15</sup>N-signatures revealed that nutrients originated almost exclusively
from sewage. Furthermore, the water balance demonstrated that >90%
of the polluted river water was diverted for irrigation, thereby threatening
food safety and groundwater quality. Per capita loads of 1.42 kgN/yr
and 115 gP/yr were comparable to the peak discharges typical of Europe
and the United States in 1970â1990, but concentrations were
2â3 times higher in the BeijingâTianjin region. Our
research identified sewage as the predominant nutrient source in this
semiarid region, which suggests that state-of-the-art wastewater treatment
would drastically mitigate eutrophication and even more rapidly than
was previously observed in Europe
Organic Micropollutants in Rivers Downstream of the Megacity Beijing: Sources and Mass Fluxes in a Large-Scale Wastewater Irrigation System
The Haihe River System (HRS) drains the Chinese megacities
Beijing
and Tianjin, forming a large-scale irrigation system severely impacted
by wastewater-borne pollution. The origin, temporal magnitudes, and
annual mass fluxes of a wide range of pharmaceuticals, household chemicals,
and pesticides were investigated in the HRS, which drains 70% of the
wastewater discharged by 20 million people living in Beijing. Based
on Chinese consumption statistics and our initial screening for 268
micropollutants using high-resolution mass spectrometry, 62 compounds
were examined in space and time (2009â2010). The median concentrations
ranged from 3 ng/L for metolachlor to 1100 ng/L for benzotriazole
and sucralose. Concentrations of carbendazim, clarithromycin, diclofenac,
and diuron exceed levels of ecotoxicological concern. Mass-flux analyses
revealed that pharmaceuticals (5930 kg/year) and most household chemicals
(5660 kg/year) originated from urban wastewaters, while the corrosion
inhibitor benzotriazole entered the rivers through other pathways.
Total pesticide residues amounted to 1550 kg/year. Per capita loads
of pharmaceuticals in wastewater were lower than those in Europe,
but are expected to increase in the near future. As 95% of the river
water is diverted to irrigate agricultural soil, the loads of polar
organic micropollutants transported with the water might pose a serious
threat to food safety and groundwater quality
Assessment and Identification of Primary Factors Controlling Yangtze River Water Quality
Challenges for rapid dam construction remain, including
pollutant
trajectories after construction, how socioeconomic developments drive
long-term water quality and large spatial changes, and which indicators
primarily control these changes. Here, high-density sampling and socioeconomic
data were integrated to assess primary factors controlling Yangtze
River water quality. Our results indicated that the pollutant trajectories
in the upper and lower sections differ, owing to the Three Gorges
Dam. From 2003 to 2020, the decreased TP, NH4+-N, and CODMn concentrations were strongly correlated
to the per capita gross domestic product, drainage pipe length, number
of wastewater treatment plants, and fertilizer consumption. Moreover,
Se and Cd concentrations decreased, whereas Ni and Zn concentrations
increased from 2007 to 2020. The water quality index (WQI) demonstrated
that Yangtze River water quality varies from levels âgoodâ
to âexcellentâ, is better in the winter, and deteriorates
with decreasing distance from the estuary. Furthermore, an optimized
WQI model consisting of six crucial parameters (TN, Pb, Cd, Zn, NO3ââN, and As) was built using the
random forest method, which exhibits excellent performance in water
quality assessment. The approach proposed in the present study can
significantly reduce the number of parameters required to assess water
quality without compromising the results