Assessing Environmental Risk Posed by Pharmaceuticals and Personal Care Products in Shallow Lakes, Florida, USA—Part B

Abstract

The use of pharmaceuticals and personal care products (PPCPs) is steadily growing as the world’s population both increases and ages. Many of these products are released into the environment via municipal wastewater treatment plants and onsite wastewater treatment systems (septic tanks). Consequently, it is essential to ascertain whether these contaminants pose any risk to aquatic organisms who live in the water bodies receiving this waste. Risk quotients (RQ) are a commonly used method to do so. For our pilot study, we undertook such analysis for three trophic levels: algae, crustaceans, and fish from two small lakes, one fed by septic tanks and the other not. This research was conducted in 2021 from the end of the dry season and through most of the wet season in west central Florida, USA. Of the 14 PPCPs measured, six had RQs that posed a risk to all three trophic levels. This risk increased during the wet season. Both lakes, regardless of whether they directly received PPCPs from septic tanks or not, had some level of risk. However, the lake without septic tanks had a smaller risk, both in elevated RQs and the occurrence to the various species. Of the PPCPs measured, DEET, caffeine, and theophylline posed the greatest risk.

1. Introduction

Pharmaceuticals and personal care products (PPCPs) are a group of chemicals widely used by a growing and aging population [1]. Most PPCPs can induce physiological effects even at low concentrations, making them highly potent compounds that can disrupt biological processes or lead to acute exposure to aquatic organisms [2,3]. One of the sources of PPCPs in the environment is through the release of treated water from onsite wastewater treatment systems (OWTS), more commonly known as septic tanks. These waters are released into rivers, lakes, and drainfields. Because of the inability of these treatment systems to remove all PPCPs from the effluent, these contaminants can be incorporated into the tissue of organisms that interact with this polluted water [4].

A widely used method to assess the potential risk of exposure from contaminants is risk quotients (RQ) [5], a ratio of maximum measured environmental concentration to the predicted no-effect concentration [6]. This method has been successfully applied to aquatic environments such as lakes [7], rivers [8], coastal waters [9], and groundwater [10]. Large lakes tend to have lower risk due to the sheer volume of water, whereas rivers and small lakes are at greater risk [8].

Our pilot study investigates the impact of OWTS on aquatic species in a small, shallow, enclosed lake in a residential area. To serve as a control, we also include a nearby, similar lake located within a nature preserve. The form of impact is PPCPs released from the OWTS surrounding the residential lake. We propose that the concentrations of PPCPs in the residential lake, as measured by the risk quotient (RQ), are at levels not detrimental to aquatic organisms. Additionally, we evaluate how environmental risk assessment varies between dry and wet seasons and whether using maximum versus mean concentration levels influences risk estimation. As this study does not include an entire year’s data and is limited to two lakes, we consider our results to be preliminary in nature.

2. Materials and Methods

2.1. Study Area

Our study was conducted in the littoral zone of two lakes in West-Central Florida. The residential lake (RL) is internally drained, 120 m wide, with a maximum depth of 5.95 m. It is surrounded by 18 residential homes equipped with OWTS for wastewater treatment. Potable water for the homes comes from wells that draw water from the Upper Floridan Aquifer (UFA). Natural lake (NL), which serves as a control site, is located 1800 m northwest of RL. It is 100 m wide and 2.8 m at its deepest point. The two lakes are similar in their geomorphology and climate setting, albeit the control lake being smaller and shallower. Within RL, sampling was conducted at three sites—Site 1 (RL-S1), Site 2 (RL-S2), and Site 3 (RL-S3)—and at one site at NL. The three sites from RL were selected because of their similarities: (1) distance of their OWTS from the lake; (2) hydraulic gradients; and (3) width of the shoreline vegetation (Figure 1).

2.2. Water Sampling and Analyses

Water samples were collected weekly from the end of the dry season (late April 2021) through to the height of the wet season (late August 2021) using 1L amber bottles. After filtration and solid phase extraction, the concentration of the PPCPs was determined through liquid chromatography mass spectrometry using multiple reaction monitoring (MRM) method, which was employed to detect and quantify the PPCP concentrations. For more details on the study area, chromatographic methods [11,12,13,14,15,16,17,18], and materials, see Bialkowska-Jelinska et al. [19] and Supplementary Materials (Tables S1–S6).

2.3. Ecological Risk Assessment

The ecological risk assessment in this study was conducted using the risk quotient (RQ) method to evaluate the potential effects of PPCPs on aquatic organisms across three trophic levels: fish, crustacean (daphnia), and algae (green algae). The RQ was calculated using the maximum PPCP concentrations detected throughout the study, including the mean and maximum values for both the dry and wet seasons.

The RQ is a widely used metric to assess the ecological risk of contaminants in aquatic ecosystems [1,20,21]. It is calculated as the ratio between the measured environmental concentration (MEC) of a compound and its predicted no-effect concentration (PNEC):

$$\mathrm{RQ}={\displaystyle \frac{\mathrm{MEC}}{\mathrm{PNEC}}}$$

(1)

$$\mathrm{PNEC}={\displaystyle \frac{\mathrm{ChV}}{\mathrm{AF}}}$$

(2)

where RQ is a risk quotient; MEC is the maximum and mean concentration of the PPCP detected in surface water; PNEC is predicted-no-effect-concentration values of PPCPs; ChV represents the chronic toxicity values; and AF stands for assessment factor and equals 100.

PNEC can also be calculated using LC50 values, which indicate the lethal concentration for 50% of a target population. ChV represents the concentration required to produce chronic effects over extended exposure. If the chronic toxicity value is not exceeded, no toxic effects are expected [22]. ChVs of analyzed PPCPs were obtained from the ‘Organic Module Report’ generated using the US EPA’s Ecological Structure-Activity Relationship (ECOSAR v2.2) software [23] and are presented in

Table 1. Chronic toxicity values for fish, crustacean, and algae.

PPCP	Chronic Toxicity Value (mg/L)
	Fish	Crustacean	Algae
Octocrylene (OCT)	0.00086	0.0081	0.042
Atorvastatin (ATV)	0.055	0.257	1.61
Fluoxetine (FLX)	0.025	0.019	0.033
Ibuprofen (IBU)	4.94	4.31	15.6
Testosterone (TST)	5.84	0.637	2.43
Propylparaben (PPB)	0.406	2	1.69
Carbamazepine (CBZ)	1.05	1.17	0.096
N,N-Diethyl-meta-toluamide (DEET)	0.49	5.72	3.21
Methylparaben (MPR)	2.06	0.99	3.89
Sulfamethoxazole (SMX)	5	0.07	11.14
Acetaminophen (APAP)	0.124	0.189	0.352
Cotinine (COT)	6.13	109	19.8
Caffeine (CAF)	0.914	2.8	2.63
Theophylline (THE)	1.49	5.55	4.13

Values extracted from ECOSAR v2.2.

.

Final RQ values were categorized as follows: low risk (RQ  <  0.1); medium risk (RQ between 0.1 and 1); and high risk (RQ  ≥  1.0) [7,21,24]. The RQ values were determined for the following scenarios:

• The maximum PPCP concentrations detected throughout the sampling campaign (RQ_max).
• The maximum PPCP concentrations recorded during the dry and wet seasons (RQ_max-dry and RQ_max-wet).
• The mean PPCP concentrations observed during the dry and wet seasons (RQ_mean-dry and RQ_mean-wet).

2.4. Statistical Analysis

An ANOVA test was conducted to evaluate whether the risk quotients for PPCPs differed significantly between the dry and wet seasons across four lake sites (Tables S7–S10).

3. Results

The maximum PPCP concentrations for Site RL-S1, RL-S2, RL-S3, and NL and mean concentrations of the six PPCPs are presented in

Table 2. Maximum PPCP concentrations found at each sampling site during the dry and wet seasons.

	PPCP Concentrations (μg/L)
	RL-S1		RL-S2		RL-S3		NL
PPCP	Dry	Wet	Dry	Wet	Dry	Wet	Dry	Wet
OCT	ND	0.99	ND	ND	ND	0.01	ND	ND
ATV	ND	0.13	ND	ND	ND	ND	ND	ND
FLX	ND	0.02	ND	0.02	ND	0.07	ND	0.01
IBU	ND	10.95	8.63	9.42	8.53	15.17	15.08	14.13
TST	0.19	8.42	31.94	1.21	1.77	0.92	22.33	48.18
PPB	ND	ND	ND	ND	ND	1.11	ND	ND
CBZ	ND	ND	ND	0.27	ND	0.54	ND	ND
DEET	4.54	22.94	4.21	15.32	4.54	17.31	182.48	76.89
MPR	ND	0.28	ND	ND	ND	ND	ND	ND
SMX	ND	0.07	0.06	0.08	ND	0.10	0.05	0.06
APAP	0.17	1.08	0.10	6.99	0.42	0.75	ND	0.67
COT	8.50	8.96	7.96	8.12	8.82	8.14	4.07	1.31
CAF	454.2	374.91	51.22	16.92	29.13	68.30	197.11	249.50
THE	33.18	371.07	53.02	7.29	28.81	298.64	46.97	151.95

ND—not detected.

and

Table 3. Mean PPCP concentrations found at each sampling site during the dry and wet seasons.

	PPCP Concentrations (μg/L)
	RL-S1				RL-S2				RL-S3				NL
PPCP	Dry	SD	Wet	SD	Dry	SD	Wet	SD	Dry	SD	Wet	SD	Dry	SD	Wet	SD
TST	5.63	7.61	2.87	2.98	8.82	15.43	0.43	0.34	0.87	0.61	0.40	0.26	9.14	10.08	6.32	12.20
DEET	3.89	0.47	13.12	4.85	3.80	0.31	8.78	3.99	3.75	0.57	9.72	4.36	53.37	86.64	14.78	18.00
APAP	0.09	0.10	0.18	0.29	0.03	0.05	0.64	2.11	0.25	0.11	0.15	0.20	0.00	0.00	0.08	0.18
COT	8.16	0.37	6.53	1.40	7.85	0.08	6.83	1.12	8.35	0.44	6.51	1.18	2.96	1.28	0.77	0.23
CAF	147.15	209.10	100.71	104.92	24.67	18.15	6.64	3.62	23.58	5.33	11.71	17.57	91.33	85.64	96.79	64.91
THE	20.54	11.98	78.23	94.93	17.37	23.81	2.67	1.96	12.18	11.30	26.82	79.00	29.49	17.07	71.01	39.15

, respectively. Not all PPCPs were detected throughout the sampling interval, with propyl paraben and atorvastatin only being present once. The highest maximum values during the entire sampling period were for caffeine, DEET, and theophylline. For the mean values, only those that were detected more than nine times (50% of samples) were included, which left only six of the PPCPs. Of these, caffeine had the highest values. For a detailed discussion of these PPCPs, please see the related article [19] in this issue.

3.1. Risk Assesment for Maxiumum PPCP Concentrations

The RQs calculated for maximum PPCP concentrations (RQ_max) at each sampling site are presented in

Table 4. RQ_max at each site during the sampling period.

	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
OCT	115.116	*	1.163	*	12.222	*	0.123	*	2.357	*	0.024	*
ATV	0.231	*	*	*	0.049	*	*	*	0.008	*	*	*
FLX	0.080	0.072	0.280	0.056	0.105	0.095	0.368	0.074	0.061	0.055	0.212	0.042
IBU	0.222	0.191	0.307	0.305	0.254	0.219	0.352	0.350	0.070	0.060	0.097	0.097
TST	0.286	0.547	0.030	0.825	2.625	5.014	0.278	7.564	0.688	1.314	0.073	1.983
PPB	ND	*	0.273	*	*	*	0.056	*	*	*	0.066	*
CBZ	0.025	0.026	0.051	*	0.022	0.023	0.046	*	0.270	0.281	0.563	*
DEET	4.673	3.127	3.533	37.241	0.400	0.268	0.303	3.190	0.713	0.477	0.539	5.685
MPR	0.014	*	*	*	0.028	*	*	*	0.007	*	*	*
SMX	0.001	0.002	0.002	0.001	0.100	0.114	0.140	0.086	0.001	0.001	0.001	0.001
APAP	0.877	5.637	0.605	0.540	0.576	3.698	0.397	0.354	0.309	1.986	0.213	0.190
COT	0.146	0.132	0.144	0.066	0.008	0.007	0.008	0.004	0.045	0.041	0.045	0.021
CAF	49.694	5.604	7.473	27.298	16.221	1.829	2.439	8.911	17.270	1.948	2.597	9.487
THE	24.904	3.558	20.043	10.198	6.686	0.955	5.381	2.738	8.985	1.284	7.231	3.679

*—PPCP not detected; RQ not applicable.

. RQ_max values for octocrylene, caffeine, theophylline, and DEET at residential lake (RL-S1, RL-S2, RL-S3) pose the highest environmental risk, with fish and crustaceans showing the most significant risk. High RQ_max values (>1) are prevalent in RL, while the risk in NL generally was lower, but driven from the same compounds. Moderate environmental risk contaminants (0.1 ≤ RQ ≤ 1), such as atorvastatin, fluoxetine, ibuprofen, sulfamethoxazole, and acetaminophen, frequently appear in crustaceans across multiple sites. Low-risk contaminants (RQ < 0.1) are mostly found in NL, with methylparaben, sulfamethoxazole, acetaminophen, and ibuprofen consistently showing minimal ecological threats.

3.2. Risk Assessment for Mean PPCP Concentrations

The RQs calculated for mean PPCP concentrations (RQ_mean) at each sampling site are presented in

Table 5. RQ_mean at each site during the sampling period.

	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
TST	0.060	0.046	0.009	0.113	0.546	0.419	0.080	1.035	0.143	0.110	0.021	0.271
DEET	2.259	1.520	1.712	4.765	0.194	0.130	0.147	0.408	0.345	0.232	0.261	0.727
APAP	0.129	0.387	0.137	0.048	0.085	0.254	0.090	0.032	0.045	0.136	0.048	0.017
COT	0.112	0.116	0.113	0.020	0.006	0.007	0.006	0.001	0.035	0.036	0.035	0.006
CAF	12.148	1.253	1.570	10.457	3.965	0.409	0.513	3.414	4.222	0.435	0.546	3.634
THE	4.390	0.442	1.582	4.146	1.179	0.119	0.425	1.113	1.584	0.160	0.571	1.496

. RQ_mean values for caffeine, theophylline, and DEET at residential lake (RL-S1, RL-S2, RL-S3) pose the highest environmental risk, with fish showing the most significant risk. High RQ_mean values (>1) are prevalent in RL, while NL generally had lower risk, except for DEET. Moderate environmental risk contaminants (0.1 ≤ RQ ≤ 1), such as caffeine, theophylline, testosterone, and DEET, frequently appear in crustaceans across multiple sites. Low-risk contaminants (RQ < 0.1) are mostly found in NL, with cotinine and acetaminophen consistently showing minimal ecological threats.

3.3. Risk Assessment for Maximum PPCP Concentrations During the Dry and Wet Seasons

Table 6. RQ_max-dry and RQ_max-wet at each site during dry and wet seasons.

Dry Season
	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
OCT	*	*	*	*	*	*	*	*	*	*	*	*
ATV	*	*	*	*	*	*	*	*	*	*	*	*
FLX	*	*	*	*	*	*	*	*	*	*	*	*
IBU	0.188	0.175	0.173	0.305	0.215	0.200	0.198	0.350	0.059	0.055	0.055	0.097
TST	0.286	0.547	0.030	0.382	2.625	5.014	0.278	3.505	0.688	1.314	0.073	0.919
PPB	*	*	*	*	*	*	*	*	*	*	*	*
CBZ	*	*	*	*	*	*	*	*	*	*	*	*
DEET	0.927	0.859	0.927	37.241	0.079	0.074	0.079	3.190	0.141	0.131	0.141	5.685
MPR	*	*	*	*	*	*	*	*	*	*	*	*
SMX	*	0.001	*	0.001	*	0.086	*	0.074	*	0.001	*	0.000
APAP	0.137	0.081	0.339	0.004	0.090	0.053	0.222	0.003	0.048	0.028	0.119	0.001
COT	0.139	0.130	0.144	0.066	0.008	0.007	0.008	0.004	0.043	0.040	0.045	0.021
CAF	49.694	5.604	3.187	21.566	16.221	1.829	1.040	7.040	17.270	1.948	1.108	7.495
THE	2.227	3.558	1.934	3.152	0.598	0.955	0.519	0.846	0.803	1.284	0.698	1.137
Wet Season
	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
OCT	115.116	*	1.163	*	12.222	*	0.123	*	2.357	*	0.024	*
ATV	0.231	*	*	*	0.049	*	*	*	0.008	*	*	*
FLX	0.080	0.072	0.280	0.056	0.105	0.095	0.368	0.074	0.061	0.055	0.212	0.042
IBU	0.222	0.191	0.307	0.286	0.254	0.219	0.352	0.328	0.070	0.060	0.097	0.091
TST	0.144	0.021	0.016	0.825	1.322	0.190	0.144	7.564	0.347	0.050	0.038	1.983
PPB	*	*	0.273	*	*	*	0.056	*	*	*	0.066	*
CBZ	0.025	0.026	0.051	*	0.022	0.023	0.046	*	0.271	0.281	0.563	*
DEET	4.673	3.127	3.533	15.686	0.400	0.268	0.303	1.344	0.713	0.477	0.539	2.394
MPR	0.014	*	*	*	0.028	*	*	*	0.007	*	*	*
SMX	0.001	0.002	0.002	0.001	0.100	0.114	0.140	0.083	0.001	0.001	0.001	0.001
APAP	0.871	5.637	0.605	0.540	0.571	3.698	0.397	0.354	0.307	1.986	0.213	0.190
COT	0.146	0.132	0.132	0.021	0.008	0.007	0.007	0.001	0.045	0.041	0.041	0.007
CAF	41.019	1.851	7.473	27.298	13.390	0.604	2.439	8.911	14.255	0.643	2.597	9.487
THE	24.904	0.489	20.043	10.198	6.686	0.131	5.381	2.738	8.985	0.177	7.231	3.679

*—PPCP not detected; RQ not applicable.

presents RQ_max-dry and RQ_max-wet. RQ_max-dry was the highest for caffeine at each trophic level, indicating high environmental risk. The highest RQ_max-dry was observed for RL-S1.

During the wet season, a greater number of PPCPs were detected in the lake waters, and more PPCPs exceeded high-risk thresholds, indicating an increase in environmental risk. During the wet season, RQ_max-wet was high in octocrylene, caffeine, theophylline, and DEET, especially at sites in RL. Moderate-risk contaminants (0.1 ≤ RQ ≤ 1) were more widespread in the wet season, affecting a larger number of species, especially crustaceans and fish.

NL generally had lower contamination levels, but DEET, caffeine, theophylline, and testosterone posed high or moderate risk across both seasons. The overall trend across seasons suggests that residential lakes remain more polluted than the natural lake, with fish being the most affected organism, followed by crustaceans and algae.

The RQ values across the four study sites demonstrate significant differences in contamination levels, with RL generally exhibiting higher risks. High environmental risk for octocrylene, caffeine, theophylline, and DEET was predominantly found in RL-S1, followed by RL-S2 and RL-S3. Moderate-risk contaminants were present across all residential lakes but were more frequent in RL-S3 and RL-S2. Low-risk contaminants were found mostly in NL.

3.4. Risk Assessment for Mean PPCP Concentrations During the Dry and Wet Seasons

The environmental risk assessed by RQ for mean PPCP concentrations varies across the four sampling sites (

Table 7. RQ_mean-dry and RQ_mean-wet at each site during dry and wet seasons.

Dry Season
	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
TST	0.096	0.151	0.015	0.157	0.884	1.385	0.137	1.435	0.232	0.363	0.036	0.376
DEET	0.793	0.776	0.765	10.892	0.068	0.066	0.066	0.933	0.121	0.118	0.117	1.663
APAP	0.073	0.024	0.202	0.000	0.048	0.016	0.132	0.000	0.026	0.009	0.071	0.001
COT	0.133	0.128	0.136	0.048	0.007	0.007	0.008	0.003	0.041	0.040	0.042	0.015
CAF	16.100	2.699	2.582	9.992	5.255	0.881	0.842	3.262	5.595	0.938	0.897	3.473
THE	1.379	1.162	0.817	3.979	0.370	0.312	0.219	0.531	0.497	0.419	0.295	0.714
Wet Season
	Fish				Crustacean				Algae
PPCP	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL	RL-S1	RL-S2	RL-S3	NL
TST	0.049	0.007	0.007	0.108	0.451	0.068	0.063	0.992	0.118	0.018	0.016	0.260
DEET	2.678	1.792	1.984	3.016	0.229	0.153	0.170	0.258	0.409	0.274	0.303	0.460
APAP	0.145	0.516	0.121	0.065	0.095	0.339	0.079	0.042	0.051	0.182	0.043	0.023
COT	0.108	0.111	0.106	0.013	0.006	0.006	0.006	0.001	0.033	0.034	0.033	0.004
CAF	11.019	0.726	1.281	10.590	3.597	0.237	0.418	3.457	3.829	0.252	0.445	3.680
THE	5.250	0.179	1.800	4.766	1.410	0.048	0.483	1.279	1.894	0.065	0.649	1.719

).

RL-S1 showed severe pollution in both dry and wet seasons. During the dry season, caffeine (RQ = 16.100) and theophylline (RQ = 1.379) presented high environmental risk for fish, while crustaceans and algae experienced significant exposure to caffeine (RQ = 5.255 and 5.595, respectively). DEET, acetaminophen, and cotinine posed a moderate environmental risk in fish. Moderate risk was posed for crustaceans and algae by testosterone and theophylline. In the wet season, RQ for caffeine decreased to 13.212, and theophylline increased to 6.007 in fish, while DEET increased to 2.622. For crustaceans and algae, theophylline increased in the wet season.

RL-S2 shows moderate contamination levels compared to RL-S1. In the dry season, caffeine and theophylline posed a high environmental risk for fish, and a moderate environmental risk in fish was posed by testosterone, DEET, and cotinine. Otherwise, the remaining contaminants presented low-risk range. The wet season increases the risk of acetaminophen and DEET in fish, moving it into the high-risk category. However, the overall increase in contamination is less pronounced than in RL-S1.

RL-S3 appears to be the least contaminated among the residential lakes. In the dry season, only caffeine poses high risk for fish (RQ_mean-dry = 2.582). Moderate risk was posed by DEET, theophylline, acetaminophen, and cotinine. During the wet season, the highest environmental risk in fish was from DEET.

For the NL, the dry season held high environmental risk to fish from DEET, caffeine, and theophylline. Daphnia’s high risk arose from caffeine, testosterone, and DEET, while green algae’s risk came from caffeine, DEET, and theophylline. Moderate risk was posed by testosterone for fish and algae. Crustacean’s moderate risk came from theophylline. In the wet season, high RQs for fish were found for caffeine, DEET, and theophylline. High risk for crustacean and algae was posed by caffeine, testosterone, theophylline, and DEET. A moderate environmental risk to fish was assessed to be testosterone and acetaminophen. Acetaminophen also posed a moderate risk for daphnia and algae.

A one-way ANOVA was conducted to assess whether there were statistically significant differences in risk quotients values. The results indicated that none of the compounds showed statistically significant variation in dry and wet seasons (Tables S7–S10).

4. Discussion

The results demonstrate that all detected PPCPs pose a high or moderate environmental risk to aquatic organisms for at least one of the trophic levels. As such, our supposition that the PPCPs pose little risk is incorrect. Our findings agree with other studies assessing environmental risk of aquatic organisms particularly for caffeine, carbamazepine, acetaminophen, and DEET [7,21,25,26,27].

4.1. Aquatic Trophic Levels and Environmental Risk Assessment

An understanding of the ecological risk that PPCPs pose to species at various trophic levels in small urban water bodies is essential for evaluating their potential impact on the ecosystem. Our results show that PPCPs present the highest risk for the uppermost trophic level (fish) in each sampling site. Predation by fish of lower trophic species provides the avenue for PPCP bioaccumulation [28]. Mojiri et al. [29] found PPCPs from various classes in tissues, blood plasma, muscle, liver, gill, and the homogenized bodies of fish in waters around the world. For our study, the apex predator is the American alligator, Alligator mississippiensis, which occupied the residential lake. This animal would be exposed to the detected PPCPs for the longest period of any species in the lake. A study of alligators hatched in a polluted Lake Apopka in Florida showed altered gonadal development, plasma hormone concentrations, and growth [30].

Planktonic crustaceans (Daphnia) have the second highest risk, followed by algae. Only for caffeine is the risk for algae slightly higher than for daphnia organisms. Daphnia’s susceptibility to PPCPs was shown by Luna et al. [31], who exposed Daphnia magna to fluoxetine over a 40-day period during which population growth rates decreased. Flaherty and Dodson [32] subjected Daphnia to sulfamethoxazole and determined a significant increase in the male/female ratio for offspring. Ecological impacts can be intensified when aquatic organisms are simultaneously exposed to multiple PPCPs [33]. The combination of individual PPCPs may result in harmful effects even when each compound is present at its no-observed-effect concentration (NOEC) [34]. Backhaus et al. [35] found that a mixture of five PPCPs caused toxicity in marine microalgal communities, despite each being at its individual NOEC.

The risk to algae posed by PPCPs comes through various processes such as chelation adsorption, ion exchange or complexation, electrostatic interaction, and microprecipitation [36,37]. Concentrations of PPCPs below two mg/L do not significantly affect algae [38]. However, some compounds, such as antibiotics and antibacterial agents, can decrease algal growth at concentrations below one mg/L, but in most cases algae can survive low concentrations of PPCPs [29]. These authors found that Nannochloris sp. green algae were very effective at removing triclosan from wastewater. Algae’s ability to effectively remove PPCPs from wastewater highlights their potential for bioremediation [39].

4.2. Seasonal Risk to Aquatic Organisms

RQ values vary between the seasons, with the larger number of PPCPs having a higher RQ in the wet season. Only testosterone had a higher RQ_max in the dry season. The variable life cycles of aquatic organisms can influence the degree of negative impact of PPCPs [40]. For example, mosquitofish (Gambusia holbrooki), which are found in both lakes, are reproductively active from spring to fall. During the winter, the female fish store the sperm, and the offspring fertilizes in the spring [40]. Elevated testosterone and cotinine can impact these aquatic organisms during hatching and in the wet season influence the organism’s adult life cycle, thereby adversely affecting survival rates. Seasonal spikes in the contamination we found could affect population dynamics and ecosystem stability, highlighting the critical need for monitoring and managing PPCP levels during this vulnerable time for aquatic life.

4.3. Concentration Level: Maximum or Mean?

Maximum RQs highlight the worst-case ecological scenario, especially if the lake might have a potentially sensitive species to elevated PPCP levels. This study provides a precautionary approach to environmental management. As many PPCPs have not been tested for their toxicity to aquatic organisms, calculating the maximum RQ value provides some mechanism for testing the state of risk [41]. An inherent limitation of concentrating on only maximum values is that having one short-term spike in PPCPs, while otherwise values are relatively low, could suggest a more dire situation than is actually the case. Conversely, using mean RQ concentrations removes the influence of both the highest and lowest values, which could create a situation of undue alarm or a sense of complacency.

From an environmental management perspective, regular monitoring of PPCP concentrations in lake waters using RQs is needed to reduce the likelihood of unexpected environmental degradation of our lakes [42]. As shown in our study, sampling only several times a year will create an inaccurate view of the state of the risk posed to aquatic organisms.

4.4. Assumptions and Limitations

We calculated the RQ values using predicted chronic toxicity values (ChV) derived from the ECOSAR model. Hence, it should be recognized that this prediction results in the RQs being estimates. For consistency and to streamline the assessment process, we used exclusively the ECOSAR-derived ChVs as the source of toxicity information for this analysis [21]. This model/program is commonly used by the US EPA, from which we infer our approach is justified; the agency updated its ECOSAR software in 2024. This method is also recommended in the Guidelines on Environmental Risk Assessment of the European Medicines Agency. We recognize there are other approaches that are better suited to chronic exposures. For example, Raimondo and Forbes [43] suggest the use of other comprehensive modeling frameworks, such as the Population Modeling Guidance for Use, Interpretation, and Development in Ecological Risk Assessment (Pop-GUIDE), which offers better leverage of existing data for evaluating potential ecological risks.

There are several limitations to using RQs for determining environmental hazards to any species. First, many of the studies on fish are conducted in laboratory settings, which have certain drawbacks [44]. These studies only capture a narrow view of the complexity of natural environments and the dynamic processes involved. Interactions and conditions in the natural environment are far more variable and intricate than those in a laboratory. Therefore, many of the processes related to PPCPs and aquatic life are not yet fully understood. Additionally, laboratory experiments often have short durations and cannot measure chronic effects that may take many months to become apparent. However, these studies are important first steps for determining the effects of PPCPs due in part to the vast numbers of these contaminants. Second, risk quotients do not describe what the actual risk is to the organism being exposed to contaminants [45]. Third, Raimondo and Forbes [43] strongly suggest that RQs are too simplistic for assessing chronic risks and there is a need to use population models for more accurate assessments that can help inform better regulatory decision-making. The USEPA acknowledges that RQs are not necessarily correlated with the magnitude or risk [46].

We recognize that using data from only two lakes restricts our ability to make definitive conclusions and incorporating more lakes would be optimal. As such, we consider this research as a pilot study to guide future investigations. Additionally, an entire year’s worth of data could provide a better understanding of the dry season; however, the focus of the study was the onset of the wet season. Also, a greater suite of PPCPs could have been analyzed, but once again, time and cost were limiting factors. Finally, investigating the impact of individual precipitation events may provide insight into extreme events, but their short time span might not be significant for the chronic impact on the health of the lake species.

5. Conclusions

Our results found that the concentrations of PPCPs in the residential lake, as defined by the risk quotient, pose an environmental risk to the aquatic organisms. The results demonstrated that all the detected PPCPs in the lakes present a high or moderate environmental risk to aquatic organisms, which include one species from each trophic level: algae, daphnia, and fish. We should stress that this research should be considered a pilot study. To address the limitations listed above, we recommend the following: (1) increase the sampling period to a full year to provide a better understanding of how PPCP concentrations change after the end of the wet season; (2) incorporate more lakes to produce more definitive conclusions; (3) increase the number of PPCPs analyzed; and (4) incorporate population models in determining risk.