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After three decades of reform and opening up, China’s economy has experienced huge changes. Against the background of economic globalization, foreign direct investment (FDI) plays an important role in China’s economy. China has become one of the world’s largest FDI inflow countries, which has had an important impact on its economic development. FDI has preferred the industrial sector, which also has serious environmental pollution. This study will consider vertical and horizontal FDI location choice theory and conduct theoretical analysis concerning the FDI location choice within the industrial sectors, as well as empirical analysis to test the distribution of FDI in pollution-intense industries. Furthermore, the “Catalog of Industries for Foreign Investment” is one of China’s important industrial policies to guide foreign investment. Since being implemented in 1995, it has made five adjustments. The analysis of the distribution of FDI in the polluting industries and the impact of the change process will provide advice instructive for the government to amend the catalog.

Environmental economics has typically adopted two approaches to the demonstration of the optimal level of pollution. The first superimposes a marginal pollution cost (MPC) function on the traditional model of the profit maximising firm and demonstrates that Pareto optimality requires the output price to be set equal to marginal social cost (MSC), defined as the sum or marginal private cost (MC) and marginal pollution cost. The second looks at the marginal pollution cost and compares it to the marginal cost of pollution control (MPCC). The optimum in this approach then exists when marginal pollution cost equals marginal cost of pollution control.

A quantitative approach for construction pollution control that is based on construction resource levelling is presented. The parameters of construction pollution index (CPI) and hazard magnitude (hi) are treated as a pseudo resource and integrated with a project’s construction schedule. When the level of pollution for site operations exceeds the permissible limit identified by a regulatory body, a Genetic Algorithm (GA) enhanced levelling technique is used to re‐schedule project activities so that the level of pollution can be re‐distributed and thus reduced. The GA enhanced resource levelling technique is demonstrated using 20 on‐site construction activities in a project. Experimental results indicate that the proposed GA enhanced resource levelling method performs better than the traditional resource levelling method used in MS Project©. The proposed method is an effective tool that can be used by project managers to reduce the level of pollution at a particular period of time; when other control methods fail.

Purpose – This study investigates the effect of heterogeneity in an environment with a dynamic public bad.

Methodology/approach – Every period agents decide on own level of production that generates private revenue and emissions. Emissions lead to pollution that acts as a public bad and accumulates over time. Our treatment variable is the emission propensity of agents' production technologies. We characterize the Markov perfect equilibrium and social optimum and employ a laboratory experiment to compare the observed behavior to theoretical predictions.

Findings – We find that the observed production levels are between the Markov perfect equilibrium and social optimum. With experience, the strongest adjustment and lowest level of pollution is achieved in the heterogeneous treatment with high average emission propensity. When the costs of climate change are not severe, institutions are most necessary to create incentives for environmentally friendly behavior.

Research limitations/implications – The results of this study apply to the case when heterogeneity is exogenous and the only way to reduce emissions is by reducing production. Natural extensions include the option to invest in clean technologies, the availability of communication, the group size, and endogenously emerging and exogenous regulatory institutions.

Practical implications – Our results suggest that under relatively favorable conditions heterogeneous countries are less likely to achieve sustainability without external enforcement. Under unfavorable conditions the impending common threat of significant damage leads to higher levels of voluntary cooperation.

Originality/value of the chapter – This is the first study to address the practical problem of coordination among technologically diverse countries, and fundamental questions regarding the effect of heterogeneity in environments with a dynamic public bad.

This chapter investigates how international trade affects pollution using annual data from 34 Asian countries for the period 1970–2019. Following the work of Antweiler, Copeland, and Taylor (2001), the authors divide the impact into three effects – scale, technique, and composition effects. The scale of economic activity drives pollution demand. The technique effect reflects increased willingness to bear the costs of abating pollution as a country gets more prosperous because of increased international trade. International trade changes the composition of output in a country and therefore the level of pollution as different goods are produced with different pollution intensities. This is called the composition effect. This chapter measures pollution using carbon dioxide emissions (metric tons per capita) obtained from the United States Energy Information Administration. This study estimates a regression model that provides estimates of the magnitudes of trade’s impact on pollution as per the aforesaid three effects. The authors find that the scale and the composition effects of pollution are positive, but the technique effect is negative, and that the net effect is negative (international trade leads to a lower level of emission) when the underlying model is linear, but it is positive (international trade leads to a higher level of emission when non-linearities are considered).

Recent years have produced significant demand for geographical contributions to the study of social movements in general and of environmental social movement organizations (ESMOs) in particular. Geographical approaches to the study of ESMOs emphasize “the mediation of social movement agency by place” (Miller, 2000; Routledge, 1993) and call attention to the role of place-based environmental knowledge (EK) in the broader “struggle(s) over meaning” that increasingly constitute environmental politics (Buechler, 1997; Escobar, 1992; Rangan, 2000; Watts, 1990). My chapter responds to this call by providing an examination of the reproduction of EK by antipollution organizations in India’s central Ganges River Basin (GRB). Through interviews with organization leaders and members, along with analysis of organizational websites and publications, I examine the EK of two key antipollution organizations in the GRB: The Sankat Mochan Foundation (SMF) and Kanpur Eco-Friends (KEF). Analysis focuses on methods of knowledge reproduction employed by each organization, their respective framing practices, and the localized natures of the EK they reproduce. I argue that each organization works to reproduce a specific and place-based understanding of pollution in the GRB that informs their framing of the pollution problem, the tactical activities in which their members engage, and the power relations that exist between the two organizations and their leaders. Further, I argue that engaging with EK as both a method of understanding pollution and a tactic for consolidating political power is essential to making sense of the relative success of these movement organizations and the challenges they face in trying to build a broader coalition and mass-mobilization against pollution in the Ganges.