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PM 2.5 emissions caused by household activities are considered to be important drivers of haze formation, and indirect activities closely related to industrial structure account for a large proportion of them. This article quantifies the indirect effects on energy usage and PM 2.5 emissions of urban and rural residents’ lifestyles in China during 2005-2015 according to the application of consumer lifestyle analysis. The results show that during this period, the degree of indirect impact on energy consumption of residents’ living was 2.44-2.71 times as of direct impact, and there are large regional differences between those two impacts. PM 2.5 emissions from energy consumption per unit of households in North, Northeast and Northwest China are higher than that in other regions, while energy consumption in South China is relatively environmentally friendly. Residential, clothing and transportation are the most energy-intensive and PM 2.5-intensive activities among all indirect energy consumption activities. This is the first time that the CLA method has been used to analyze and calculate PM2.5 emissions caused by household energy consumption in a wide area of China through data collection over a longer period. The calculation results are more accurate than previous studies using other methods. Also, it provides factual evidence for key policies of energy saving and environmental protection, as well as pointing out the main sectors of household energy consumption that caused high PM 2.5 emissions for specific regions. The above contributions can provide a theoretical basis and accurate reference data for governments to more purposefully guide the transformation of energy-intensive industries represented by residence and other industries and improve technology to reduce their emissions.Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively ‘hotspots’), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or ‘targeted’ for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models – differing with respect to inputs, structure, and parameterization – facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%-46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Rilematovir nmr Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.Several emerging contaminants are currently used in an unregulated manner worldwide, resulting in their increasing stringent limits in water by regulatory bodies. Thus, more viable and cheap treatment technologies are required. Recently, synergistic combinations of low-cost adsorbents have shown huge potential for aqueous toxic metals adsorption in water treatment processes. However, there is dearth of data on their potential for emerging contaminant removal. Here, low-cost kaolinite (KAC) clay was synergistically combined with blended Carica papaya or pine cone seeds, and calcined to obtain composites of KAC-Carica papaya seeds (KPA) and KAC-pine cone seeds (KPC). These adsorbents were characterized and evaluated for ivermectin adsorption at varying operating times (15-1440 min), pH (3-11), concentration (100-600 μg/L), and temperature (19.5-39.5 °C), as well as testing adsorbents’ reusability. The composites exhibited marked property differences including over 250% cation exchange capacity increases and ≥505.8 μg/g, respectively. The KPC was better at reducing ivermecitn in low-concentration solution (≈75 μg/L) to less than 5.0 μg/L compared with KPA with ≈20.0 μg/L. Though KPC showed better efficiency in adsorption capacity and lowering concentration in low-concentration solutions, KPA exhibited better reusability with 83.5 and 67.5% initial adsorption strengths remaining in the second and third adsorption cycles, respectively, compared to the 73.8 and 58.8% for the KPC. These results indicate that KPA and KPC composites have the economic potential for application in water treatment processes.It has been observed that project-based firms (PBFs) cause serious environmental problems. In order to reduce the negative impact on the environment, PBFs pay more attention to green innovations. This study investigated how top management team (TMT) cognitive framing (i.e. capability development, organizational identity, and corporate social responsibility) and emotional framing (i.e. threat, ambivalence and opportunity) influence the adoption of green innovations in PBFs. Using the method of multi-value Qualitative Comparative Analysis (mvQCA), the research analyzed the data from 29 cases in China. The results showed that in PBFs, the TMT with an expanded cognitive framing and an ambivalent emotional framing and the TMT with a moderately flexible cognitive framing and an opportunity emotional framing will adopt green innovations. On the contrary, the TMT with a moderately flexible cognitive framing and a threat emotional framing and the TMT with a contracted cognitive framing will not adopt green innovations.