Attribution of Air Quality Benefits to Clean Winter Heating Policies in China: Combining Machine Learning with Causal Inference.

Heating is a major source of air pollution. To improve air quality, a range of clean heating policies were implemented in China over the past decade. Here, we evaluated the impacts of winter heating and clean heating policies on air quality in China using a novel, observation-based causal inference approach. During 2015-2021, winter heating causally increased annual PM2.5, daily maximum 8-h average O3, and SO2 by 4.6, 2.5, and 2.3 µg m-3, respectively. From 2015 to 2021, the impacts of winter heating on PM2.5 in Beijing and surrounding cities (i.e., "2 + 26" cities) decreased by 5.9 µg m-3 (41.3%), whereas that in other northern cities only decreased by 1.2 µg m-3 (12.9%). This demonstrates the effectiveness of stricter clean heating policies on PM2.5 in "2 + 26" cities. Overall, clean heating policies caused the annual PM2.5 in mainland China to reduce by 1.9 µg m-3 from 2015 to 2021, potentially avoiding 23,556 premature deaths in 2021.

Cross-country risk quantification of extreme wildfires in Mediterranean Europe.

We estimate the country-level risk of extreme wildfires defined by burned area (BA) for Mediterranean Europe and carry out a cross-country comparison. To this end, we avail of the European Forest Fire Information System (EFFIS) geospatial data from 2006 to 2019 to perform an extreme value analysis. More specifically, we apply a point process characterization of wildfire extremes using maximum likelihood estimation. By modeling covariates, we also evaluate potential trends and correlations with commonly known factors that drive or affect wildfire occurrence, such as the Fire Weather Index as a proxy for meteorological conditions, population density, land cover type, and seasonality. We find that the highest risk of extreme wildfires is in Portugal (PT), followed by Greece (GR), Spain (ES), and Italy (IT) with a 10-year BA return level of 50'338 ha, 33'242 ha, 25'165 ha, and 8'966 ha, respectively. Coupling our results with existing estimates of the monetary impact of large wildfires suggests expected losses of 162-439 million € (PT), 81-219 million € (ES), 41-290 million € (GR), and 18-78 million € (IT) for such 10-year return period events. SUMMARY: We model the risk of extreme wildfires for Italy, Greece, Portugal, and Spain in form of burned area return levels, compare them, and estimate expected losses.

The EV revolution: The road ahead for critical raw materials demand.

Mass adoption of electric vehicles (EVs) is anticipated in the years ahead, driven primarily by policy incentives, rising incomes, and technological advancements. However, mass adoption is predicated on the availability and affordability of the raw materials required to facilitate this transformation. The implications of material shortages are currently not well understood and previous research tends to be limited by weak representation of technological change, a lack of regional disaggregation, often inflexible and opaque assumptions and drivers, and a failure to place insights in the broader context of the raw materials industries. This paper proposes a CoMIT (Cost, Macro, Infrastructure, Technology) model that can be used to analyse the impact of mass EV adoption on critical raw materials demand and forecasts that, by 2030, demand for vehicles will increase by 27.4%, of which 13.3% will be EVs. The model also predicts large increases in demand for certain base metals, including a 37 and 18-fold increase in demand for cobalt and lithium (relative to 2015 levels), respectively. Without major changes in certain technologies, the cobalt and lithium supply chains could seriously constrain the widespread deployment of EVs. Significant demand increases are also predicted for copper, chrome and aluminium. The results also highlight the importance of China in driving demand for EVs and the critical materials needed to produce them.

Suggestions for a Covid-19 Post-Pandemic Research Agenda in Environmental Economics.

In this article we draw upon early lessons from the 2020 Covid-19 crisis and discuss how these may relate to a future research agenda in environmental economics. In particular, we describe how the events surrounding the Covid-19 crisis may inform environmental research related to globalization and cooperation, the green transition, pricing carbon externalities, as well as the role of uncertainty and timing of policy inventions. We also discuss the implications for future empirical research in this area.

The Impact of the Wuhan Covid-19 Lockdown on Air Pollution and Health: A Machine Learning and Augmented Synthetic Control Approach.

We quantify the impact of the Wuhan Covid-19 lockdown on concentrations of four air pollutants using a two-step approach. First, we use machine learning to remove the confounding effects of weather conditions on pollution concentrations. Second, we use a new augmented synthetic control method (Ben-Michael et al. in The augmented synthetic control method. University of California Berkeley, Mimeo, 2019. https://arxiv.org/pdf/1811.04170.pdf) to estimate the impact of the lockdown on weather normalised pollution relative to a control group of cities that were not in lockdown. We find NO 2 concentrations fell by as much as 24  µ g/m 3 during the lockdown (a reduction of 63% from the pre-lockdown level), while PM10 concentrations fell by a similar amount but for a shorter period. The lockdown had no discernible impact on concentrations of SO 2 or CO. We calculate that the reduction of NO 2 concentrations could have prevented as many as 496 deaths in Wuhan city, 3368 deaths in Hubei province and 10,822 deaths in China as a whole.

Assessing the Economic Benefits of Flood Defenses: A Repeat-Sales Approach.

In this article we identify the impact of the construction of flood defenses on property prices using a difference-in-differences repeat-sales methodology. Our data set contains information on over 12 million individual property transactions, which is merged with GIS data identifying the spatial location and main characteristics of 1,666 flood defenses built in England between 1995 and 2014. Results suggest that at the finer 6-digit postcode level the construction of flood defenses raises urban house prices by 12.6% to 16.7%. However, for rural properties at the slightly coarser 5-digit postcode level the construction of defenses reduces house prices by 0.8% to 5.0%. This suggests that in certain locations the disamenity impact of flood defenses and the perceived threat of redirected flooding outweigh the benefits of reduced flood risk.

The environmental actions of firms: examining the role of spillovers, networks and absorptive capacity.

In the light of climate uncertainty and growing concern for the natural environment, an increasingly important aspect of global business is the environmental behaviour of firms. In this paper we consider the factors that influence firms' environmental actions (EAs). Our study of Argentinean firms concentrates on measures of environmental spillovers, informal and formal networks and absorptive capacity by testing four related hypotheses. We find that foreign-owned firms, large firms and those with a greater capacity to assimilate new environmental technologies are more likely to adopt EAs. We also show that formal and informal networks aid the adoption of EAs in the presence of traditional firm-level spillovers. Finally, we show that foreign-owned firms have different motives to domestic firms for undertaking EAs.

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (O x = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

Financial viability of electric vehicle lithium-ion battery recycling.

Economically viable electric vehicle lithium-ion battery recycling is increasingly needed; however routes to profitability are still unclear. We present a comprehensive, holistic techno-economic model as a framework to directly compare recycling locations and processes, providing a key tool for recycling cost optimization in an international battery recycling economy. We show that recycling can be economically viable, with cost/profit ranging from (-21.43 - +21.91) $·kWh-1 but strongly depends on transport distances, wages, pack design and recycling method. Comparing commercial battery packs, the Tesla Model S emerges as the most profitable, having low disassembly costs and high revenues for its cobalt. In-country recycling is suggested, to lower emissions and transportation costs and secure the materials supply chain. Our model thus enables identification of strategies for recycling profitability.