Effects of Policy for Controlling Agricultural Non-Point Source Pollution in China: From a Perspective of Regional and Policy Measures Differences.

The concerns about the contradiction between agricultural production and Agricultural Non-Point (ANPS) pollution has become increased with economic development in China. Government interventions are key to controlling ANPS pollution through the establishment of laws and policies. This paper uses the entropy method to calculate the emissions amount of ANPS pollution and policy strength of 31 provinces from 2010 to 2019 in China. The dynamic panel data model with system generalized moment is used to estimate the impacts of policies with different measures on ANPS pollution emission. According to our findings, China's policies have been helpful in controlling ANPS pollution though there are important regional differences. Moreover, four types of policy measures all contribute to the reduction in ANPS pollution. These findings improve our understanding of the relationship between policies and ANPS pollution in the analyzed period, thus providing support for the formulation of pollution management strategies in the next stage.

Has Carbon Emissions Trading Reduced PM2.5 in China?

China today has an urgent need to develop low-carbon policies that also address local air pollution. This study uses a difference-in-differences model to estimate the extent to which China's Emissions Trading Scheme (ETS), which directly addresses CO2 emissions, has also generated cobenefits by reducing PM2.5. Using monthly PM2.5 concentration and weather data for 297 Chinese cities from January 2005 to December 2017, we find that (1) China's ETS has reduced PM2.5 concentrations by 4.8%, and this reduction effect is strongest in summer. The results are confirmed by robustness tests including propensity score matching, mahalanobis distance matching, two placebo tests, and controlling atmospheric policies. (2) The ETS pilots have positive spillovers on neighboring nonpilot cities within 300 km of the pilot cites, especially for those downwind neighboring nonpilot cities, and the ETS's cobenefits are primarily a result of firms adopting abatement activities and adjusting industrial structure. (3) The cobenefits of China's ETS pilots are greater in regions with larger carbon trading volume and higher carbon trading price. (4) The reduction in PM2.5 concentration caused by China's ETS may have avoided 23,363 deaths and saved $41.38 billion annually in GDP.

A coupled recreational anglers' decision and fish population dynamics model.

The effective management of fish populations requires understanding of both the biology of the species being managed and the behavior of the humans who harvest those species. For many marine fisheries, recreational harvests represent a significant portion of the total fishing mortality. For such fisheries, therefore, a model that captures the dynamics of angler choices and the fish population would be a valuable tool for fisheries management. In this study, we provide such a model, focusing on red drum and spotted seatrout, which are the two of the main recreational fishing targets in the Gulf of Mexico. The biological models are in the form of vector autoregressive models. The anglers' decision model takes the discrete choice approach, in which anglers first decide whether to go fishing and then determine the location to fish based on the distance and expected catch of two species of fish if they decide to go fishing. The coupled model predicts that, under the level of fluctuation in the abundance of the two species experienced in the past 35 years, the number of trips that might be taken by anglers fluctuates moderately. This fluctuation is magnified as the cost of travel decreases because the anglers can travel long distance to seek better fishing conditions. On the other hand, as the cost of travel increases, their preference to fish in nearby areas increases regardless of the expected catch in other locations and variation in the trips taken declines. The model demonstrates the importance of incorporating anglers' decision processes in understanding the changes in a fishing effort level. Although the model in this study still has a room for further improvement, it can be used for more effective management of fish and potentially other populations.

Practical precautionary resource management using robust optimization.

Uncertainties inherent in fisheries motivate a precautionary approach to management, meaning an approach specifically intended to avoid bad outcomes. Stochastic dynamic optimization models, which have been in the fisheries literature for decades, provide a framework for decision making when uncertain outcomes have known probabilities. However, most such models incorporate population dynamics models for which the parameters are assumed known. In this paper, we apply a robust optimization approach to capture a form of uncertainty nearly universal in fisheries, uncertainty regarding the values of model parameters. Our approach, developed by Nilim and El Ghaoui (Oper Res 53(5):780-798, 2005), establishes bounds on parameter values based on the available data and the degree of precaution that the decision maker chooses. To demonstrate the applicability of the method to fisheries management problems, we use a simple example, the Skeena River sockeye salmon fishery. We show that robust optimization offers a structured and computationally tractable approach to formulating precautionary harvest policies. Moreover, as better information about the resource becomes available, less conservative management is possible without reducing the level of precaution.