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Whether carbon emissions trading system promotes green development is important, especially from the land supply perspective. This paper investigates the effects of the carbon emissions trading pilot program on the land supply of the energy-intensive industries using the difference-in-difference approach, based on a big land-transaction dataset for the Chinese land market from 2007 to 2017. This paper finds that the carbon emissions trading program decreases the supply of energy-intensive industries' land by 25%, suggesting that it promotes the green development. Local governments' behavior affects the supply of energy-intensive industrial land. check details Industry structure dependence reinforce the effects of the carbon emissions trading program. The impacts of the carbon emissions trading program on the supply of energy-intensive industrial land would be less in cities with stronger regional competition, higher fiscal pressure or during political cycles. This study implies that the supply of energy-intensive industrial land can be used as an indicator for evaluating the effects of the carbon emissions trading system from the factor input perspective. The incentives of local government should be considered for understanding and assessing the effects of the carbon emissions trading system on land supply for future study.Anthropogenic activities can have a great influence on water quality and in the availability of habitat and food resources, which can promote changes in the trophic diversity and carbon sources sustaining aquatic communities. The objective of this study was to evaluate if the trophic diversity and the main carbon sources sustaining fish communities change along a pollution gradient. The study was carried out at eight sites distributed along the Rio das Velhas, a Brazilian river highly impacted by anthropogenic activities, in which the discharge of domestic and industrial sewage from the Metropolitan Region of Belo Horizonte (MRBH) presents a major source of pollution. Using carbon (δ13C) and nitrogen (δ15N) isotope ratios, we identified the major carbon sources/food sources of common fish species and calculated six metrics of trophic diversity. Autochthonous primary producers (algae, periphyton, and macrophytes) were the main carbon sources for all trophic guilds at all sites, but notably, sewage-derived organic matter was an additional significant carbon source to the fish community in the most polluted testing site. Here, the community was composed mainly by detritivorous and omnivorous fishes and exhibited greater ranges of carbon and nitrogen isotopic values, large total areas, high trophic diversity, small trophic redundancy, and less even distribution of trophic niches than the less polluted sites. We conclude that the trophic guilds, trophic diversity metrics, and carbon sources sustaining fish communities in the Rio das Velhas are highly influenced by the presence of pollution. Besides favoring omnivorous and detritivorous fishes, the input of sewage also provided an important food source to sustain the fish community from sites close to the MRBH.In this paper, a sustainability evaluation method for food-packaging systems is proposed. First, food waste due to poor emptiability was determined. Then, these quantities were included in life cycle assessments (LCA) and life cycle costing (value added, VA) of the products. Finally, LCA and VA results were combined using multi-criteria decision analysis, Technique for Order by Similarity to Ideal Solution (TOPSIS), in order to identify the most sustainable food packaging system. As a case study, four different ketchup products were examined. For ketchup in polypropylene bottles, FLW resulting from poor emptiability ranged from 13.12% (±2.05) to 28.80% (±3.30) respectively, while this was only 3.85% (±0.41) for ketchup packaged in glass. After integrating the emptiability results into life cycle assessments, this resulted in greenhouse gas emissions of 5.66 to 9.16 kg CO2eq per 3.80 kg consumed ketchup, the average consumption per capita in Austria. Importantly, poor emptiability of the examined products led to greater environmental impacts than the associated packaging. While greater product loss also pushes up the costs for consumers, it contributes to more value added to the economic system, which is in stark contrast to the goal of decoupling the economy from resource consumption.Over 2 million mostly rural Americans are at risk of drinking water from private wells that contain arsenic (As) exceeding the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level (MCL) of 10 micrograms per liter (μg/L). How well existing treatment technologies perform in real world situations, and to what extent they reduce health risks, are not well understood. This study evaluates the effectiveness of household As treatment systems in southern-central Maine (ME, n = 156) and northern New Jersey (NJ, n = 94) and ascertains how untreated well water chemistry and other factors influence As removal. Untreated and treated water samples, as well as a treatment questionnaire, were collected. Most ME households had point-of-use reverse-osmosis systems (POU RO), while in NJ, dual-tank point-of-entry (POE) whole house systems were popular. Arsenic treatment systems reduced well water arsenic concentrations ([As]) by up to two orders of magnitude, i.e. from a median of 71.7 to 0.8 μg/L and from a mean of 105 to 14.3 μg/L in ME, and from a median of 8.6 to 0.2 μg/L and a mean of 15.8 to 2.1 μg/L in NJ. More than half (53%) of the systems in ME reduced water [As] to below 1 μg/L, compared to 69% in NJ. The treatment system failure rates were 19% in ME (>USEPA MCL of 10 μg/L) and 16% in NJ (>NJ MCL of 5 μg/L). In both states, the higher the untreated well water [As] and the As(III)/As ratio, the higher the rate of treatment failure. POE systems failed less than POU systems, as did the treatment systems installed and maintained by vendors than those by homeowners. The 7-fold reduction of [As] in the treated water reduced skin cancer risk alone from 3765 to 514 in 1 million in ME, and from 568 to 75 in 1 million in NJ.