Collaborating Authors


Raising standards to lower diesel emissions


Air pollution from fine particulate matter (PM2.5) is increasingly driving the global burden of disease ([ 1 ][1]), and diesel-powered vehicles are substantial contributors. Recognizing the public health impacts of diesel PM2.5 (DPM) ([ 2 ][2]), many countries have reduced emissions of DPM from both on- and off-road mobile sources over the past three decades. The previous US federal administration, however, changed course by eliminating or weakening policies and standards that govern these emissions. In contrast, the State of California has continued to reduce mobile-source DPM emissions using the state's long-standing authority under the Clean Air Act (CAA) to regulate air pollution more stringently than the federal government. Our analysis of mobile-source DPM emissions suggests that many California sector-based policies have been highly effective relative to the rest of the US. To improve health in communities disproportionately affected by these emissions, we point to opportunities to further reduce DPM emissions in California, in the US more broadly, and in parts of the world where countries have less aggressive vehicle emissions policies than the US ([ 3 ][3]). The US has targeted emissions of nitrogen oxides (NO x ) and DPM from diesel trucks and buses, railway locomotives, marine vessels, and off-road engines used in construction and agriculture through successively tighter emissions standards phased in since 1994 (table S1). These standards require low- and ultralow-sulfur diesel fuels (LSDF and ULSDF), establish emissions limits, and institute systems for portable emissions measurement and onboard diagnostics (table S1). The US Environmental Protection Agency (EPA) estimated that full implementation of Obama-era US emissions standards by 2030 would prevent some 12,000 premature deaths annually ([ 4 ][4]). Despite this, EPA leadership disbanded the PM review panel ahead of the scheduled 2020 update of federal PM standards; it also rolled back, or attempted to roll back, 85 federal air pollution policies ([ 5 ][5]) and moved to restrict the ability of states to set more stringent emissions standards ([ 6 ][6]). California, whose economy would rank fifth largest in the world if it were a sovereign nation, hosts the country's two largest ports and moves 60% of its container cargo (see supplementary materials). With the associated truck and rail traffic, California stands out as the largest emitter of DPM in the country. At the same time, California has also led the nation with the largest overall reduction in metric tons of DPM emissions from mobile sources. Over the past three decades, California's policies have systematically targeted high-emitting sectors, reducing mobile-source DPM emissions by, for example, substituting electric for diesel power where feasible, tightening emissions limits for new and existing diesel engines, and requiring ULSDF, which emits substantially less PM2.5 than higher-sulfur fuels upon combustion and can be combined with particle filters to further reduce emissions. To understand the impact of California's portfolio of policies, we used DPM emissions data from the EPA National Emissions Inventory (NEI), which assembles a comprehensive estimate of air pollution emissions using data reported by states, combined with modeled and measured inputs. We compared mobile-source DPM emissions in California versus the rest of the US for the period 1990 to 2014, the earliest and most recent year for which consistent NEI data are available ([ 7 ][7]). During that time, California reduced overall mobile-source DPM emissions by 78% while the rest of the US saw only a 51% reduction. These reductions came despite a concurrent steady rise in diesel fuel consumption: 20% in California and 28% in the rest of the US (data S1). Emissions reductions from heavy-duty diesel vehicles (HDDVs)—commercial trucks and buses—caused most of this decline, accounting for 67% of DPM emissions reductions in California and 57% in the rest of the US. Although the federal phase-in of ULSDF, off-road emissions standards, and the Heavy-Duty Engine and Vehicle Rule has reduced HDDV emissions across the US, California's reductions from HDDVs have been steeper and contribute even more to the overall reductions than would be predicted from the sector's size. Analyses of DPM emissions over time and the relative contributions made by each sector point to the effectiveness of California's policies that require diesel engine retrofits (adding emissions controls to existing HDDVs) and early replacement of older engines with newer, cleaner engines. Our analysis identifies three distinct phases in mobile-source DPM emissions between 1990 and 2014. Emissions fell overall from 1990 to 2001 in California and from 1990 to 2005 in the rest of the country. Reduced emissions from HDDVs contributed the largest share of the overall drop (see the figure and data S1). These changes are attributable to the introduction of LSDF nationwide, and to California's new requirements for vehicle inspections (table S2). Then, from 2001 to 2005 in California and from 2005 to 2008 in the rest of the country, emissions rose during an economic boom, driven primarily by increasing emissions from HDDVs and marine sources. Finally, overall DPM emissions once again fell, beginning in California in 2005 and in the rest of the US in 2008. The recession played a role in the early part of this drop ([ 8 ][8]), but emissions reductions continued through 2014 despite the economic recovery and the corresponding upturn in diesel use. During this final phase, California's 67% drop in DPM emissions outpaced the 40% reduction seen in the rest of the country (see the figure and data S1). Our analysis of individual sectors and each state's HDDV emissions suggests that California policies specifically targeting emissions from HDDVs and marine sources drove this decline. The later phases of California's emissions reductions correspond to the implementation of two overarching plans by the California Air Resources Board (CARB): the Diesel Risk Reduction Plan and the Emission Reduction Plan for Ports and Goods Movement (Goods Movement Plan), both of which encompassed multiple policies governing emissions from trucks and buses, ports, and off-road engines (table S2). Key policies targeting on-road HDDVs took effect in 2006 and 2007, further lowering the sulfur content of diesel fuel to 15 ppm (table S2) and tightening DPM emissions standards by 90% for new HDDVs (table S2). Beginning in 2010, with a rolling compliance period starting in 2015, all on-road HDDVs that operate in California were required to either retrofit existing engines with particle filters or replace engines older than the 2007 model year (table S2). By comparison, federal policies do not require retrofit or replacement of old diesel engines to meet emission standards, and HDDV engines typically operate for almost two decades, or about a million miles, before retirement. Our state-level analysis shows that by 2014 California HDDVs were emitting 139 metric tons of DPM for every billion vehicle-miles traveled (VMT), far less than the next-closest state (Oklahoma, 250 metric tons DPM per billion VMT) and the average in the rest of the country (345 metric tons DPM per billion VMT) (data S1). Although HDDVs remain California's largest source of DPM emissions, regulatory actions by CARB (over and above federal standards) have reduced HDDV emissions by 85% since 1990. If California's HDDV sector had followed the trajectory of other US states and DC, HDDV emissions in the state would have dropped only 58% (95% confidence interval, 52 to 64%) in that period (data S1). Also notable is the impact of two key CARB policies targeting marine sources. The 2007 At-Berth rule requires that oceangoing vessels switch to electric shore power while in port or use alternative control technologies to reduce emissions by an equivalent amount (table S2). The Cleaner Ocean Vessel fuel policy, finalized in 2008, requires that ships within 24 nautical miles of California's shoreline replace heavy fuel oil in their main engines with lower-sulfur fuels (table S2). Between 2008 and 2014, marine DPM emissions in the state dropped 51% overall (see the figure and data S1), and by 2018 emissions measured at the Port of Los Angeles had declined by 37% (fig. S3, A and B, and data S1). ![Figure][9] California versus the rest of the United States: Mobile-source DPM emissions declined differently Mobile-source diesel PM2.5 (DPM) emissions by sector in California versus the rest of the US from 1990 to 2014. HDDV, heavy-duty diesel vehicle; LDDV, light-duty diesel vehicle. All percentage changes reflect values relative to 1990 values. GRAPHIC: N. CARY/ SCIENCE By contrast, California has struggled to target diesel emissions from agriculture (table S2). The sector is responsible for up to 18% of the state's total DPM emissions from mobile sources, but it accounted for less than 1% of the total emissions reductions in California between 1990 and 2014. Although these figures do not reflect gains from voluntary tractor engine replacements that are reported differently, opportunities remain to reduce off-road farm emissions in the nation's leading agricultural state. Voluntary programs have further reduced DPM emissions beyond California's regulatory requirements. Incentives to bring engines and equipment to a standard cleaner than required by law are estimated to have reduced DPM emissions by more than 6000 metric tons since 2001 (table S2). A program established in 2006 has provided $1 billion in grants to update trucks, locomotives, and ships at berth, eliminating an estimated 2200 metric tons of DPM emissions (table S2). Like other policies targeting emissions along goods-movement corridors, this program particularly benefits neighboring communities, which tend to be lower-income communities of color (table S4). Taken together, CARB's policies reduced emissions to the extent that by 2014 California was emitting less than half the DPM that would be expected had the state followed the same trajectory as the rest of the US (fig. S2 and data S1). Correspondingly, we estimate that more than twice as many Californians would have died from DPM-attributable cardiopulmonary disease in 2014 alone if the state had not so markedly reduced emissions (data S1). The impact of targeted emissions regulation is also evident nationally, but it has come later and never as meaningfully as in California. Farming and construction emissions fell following the 2007 EPA Heavy Duty Engine and Vehicle Rule and the 2008–2015 phase-in of Tier 4 standards targeting off-road emissions from farm and construction equipment (table S1). Federal requirements for LSDF in the 1990s and ULSDF beginning in 2006 reduced HDDV emissions from both nonroad and on-road sources (table S1). In the marine sector, US coastal areas caught up to California's fuel standards in 2012 when ULSDF was required for smaller marine engines (table S1) and in 2015 for the largest vessels when requirements for lower-sulfur marine diesel came into effect in the North American Emissions Control Area established by the International Maritime Organization (table S1). By contrast, California has taken not only earlier action on marine emissions but also aggressive steps to target emissions from the many engines that pollute the air near ports, including marine auxiliary engines, short-haul trucks, cargo-handling cranes, and yard trucks (table S2). Individual states that have reduced HDDV emissions more than the national average are more likely to have adopted California's standards, as permitted under the CAA (table S5 and data S1), and the rest of the US could do the same. Coordination across states and between state and federal agencies means that methodological differences in data collection are unlikely to account for the observed differences in DPM emissions between California and the rest of the US (see supplementary materials). But how do we know that emission inventories are accurate and, furthermore, that CARB policies are responsible for the observed reductions? Field studies measuring changes in concentrations of DPM serve to ground-truth emissions inventories and substantiate the link between policy interventions and observed outcomes (table S4). For example, following the suite of interventions under the 2006 Goods Movement Plan, California communities in close proximity to goods-movement corridors saw significantly greater air quality improvements relative to non–goods-movement corridors and control areas monitored during the same time period (table S4). These findings show specific, local impacts of regulations targeting high-emitting sectors, distinguishing those changes from secular trends in air pollution and demonstrating their potential to advance environmental justice. The 2007 CARB regulation requiring retrofit or replacement of older HDDV engines for short-haul “drayage trucks” that operate at ports and railyards corresponded to a 70% reduction in black carbon emissions (a DPM proxy) and a 75% reduction in PM mass specific to drayage trucks measured in and around the ports of Oakland and Los Angeles between 2009 and 2011 (table S4). These changes mirror the emissions reductions measured in laboratory testing of the low-sulfur fuels and retrofit technologies used to meet the drayage truck standards (table S3). Likewise, the 2009 CARB requirement for low-sulfur fuels in oceangoing vessel engines operating within 24 nautical miles of the California coastline was associated with a measured 64% drop in San Francisco Bay Area concentrations of vanadium, a marker for combustion of heavy fuel oil (table S4). Sampling conducted by aircraft flying in the exhaust plume of a container ship approaching the coast showed that the fuel switch, combined with a required speed reduction, dropped DPM emissions by 90% (table S4). That these changes all occurred in the setting of continued growth in California's population, gross state product, and diesel consumption (figs. S4 and S5) further supports the assertion that the observed reductions track to the policies targeting DPM emissions. Observed emissions reductions are further corroborated by epidemiological data that link specific CARB policies to regional reductions in children's exposure to particle pollution and show corresponding improvements in both lung function and development in children with and without asthma ([ 9 ][10]). Finally, comparing HDDV sector emissions in California to the rest of the country likely underestimates the actual impact of CARB policies, which apply not only to the nearly half-million trucks and buses registered in California but also to the same number of out-of-state HDDVs estimated to drive California's highways each year ([ 10 ][11]). This requirement reduces emissions outside of California as well, although those reductions are attributed to federal policy. In California, cleaner air has not come at the expense of the state's economy, which in recent years has grown at double the average national rate ([ 11 ][12]). CARB estimates that every dollar the state has spent controlling air pollution has generated $38 in benefits attributable to reduced air pollution–related illness, premature death, and lost productivity. California's overall economic gain from health benefits linked to air pollution reduction, including CARB rules and programs, is estimated to have exceeded $250 billion between 1973 and 2014 ([ 12 ][13]). The link between PM2.5 exposure and increased risk of hospitalization and death from COVID-19 ([ 13 ][14]) further underscores the public health importance of cleaner air, particularly for communities of color that are disproportionately affected by both. California could benefit from additional measures to reduce emissions from off-road sectors, such as construction and agriculture, which CARB has not tackled as aggressively ([ 14 ][15]). Indeed, the nation as a whole could reduce mobile-source DPM emissions by requiring ships at berth to use shore power, and by requiring replacement or retrofit of existing on-road and off-road HDDVs in advance of fleet turnover. Given the long service life of older, dirty diesel engines, the current federal policy of mandating engine upgrades only with vehicle turnover is simply too slow. As the US initiates new federal rule-making on the proposed Cleaner Trucks Initiative to reduce NO x emissions from HDDVs, industry and environmental groups are calling on EPA to address NO x and DPM emissions in tandem and to create consistent “50-state” standards ([ 15 ][16]). In doing so, the EPA should align with CARB rules. EPA should also remove federal preemption of state emissions limits for off-road engines used in construction and agriculture. Even absent more aggressive federal policy, states' authority to set and implement their own stricter emissions standards must be protected. [][17] 1. [↵][18]GBD 2017 Risk Factor Collaborators, Lancet 392, 1923 (2018). [OpenUrl][19][CrossRef][20][PubMed][21] 2. [↵][22]California Air Resources Board, “Overview: Diesel Exhaust & Health”; [][23]. 3. [↵][24]European Union Directorate-General for Internal Policies, Comparative Study on the Differences Between the EU and US Legislation on Emissions in the Automotive Sector (2016); [\_STU(2016)587331\_EN.pdf][25]. 4. [↵][26]DieselNet, “Emission Standards, United States”; [][27]. 5. [↵][28]1. J. M. Samet, 2. T. A. Burke , Annu. Rev. Public Health 41, 347 (2020). [OpenUrl][29] 6. [↵][30]1. C. Davenport , “Trump to Revoke California's Authority to Set Stricter Auto Emissions Rules.” New York Times, 17 September 2019; [][31]. 7. [↵][32]US Environmental Protection Agency, “National Emissions Inventory (NEI)”; [][33]. 8. [↵][34]1. D. Q. Tong et al ., Atmos. Environ. 107, 70 (2015). [OpenUrl][35] 9. [↵][36]1. F. Gilliland et al ., “The Effects of Policy-Driven Air Quality Improvements on Children's Respiratory Health” (2017); [][37]. 10. [↵][38]California Air Resources Board, “Staff Report: Initial Statement of Reasons for Proposed Rulemaking: Proposed Regulation for In-Use On-Road Diesel Vehicles” (2008); . 11. [↵][39]Next10, 2017 California Green Innovation Index (2017); [][40]. 12. [↵][41]California Air Resources Board, Fifty Year Air Quality Trends and Health Benefits; [][42]. 13. [↵][43]1. X. Wu, 2. R. C. Nethery, 3. M. B. Sabath, 4. D. Braun, 5. F. Dominici , Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Sci. Adv. 6, eabd4049 (2020). 10.1126/sciadv.abd4049pmid:33148655 [OpenUrl][44][FREE Full Text][45] 14. [↵][46]California's construction emissions declined markedly from 2008 to 2011. Although industry likely lowered emissions in anticipation of deadlines in the 2008 In-Use Off-Road Diesel-Fueled Fleet Regulation (table S2), the majority of the decline is likely attributable to CARB's 2011 construction inventory revision prompted by the regulated industry. In that year, the regulation was also amended to delay implementation by 4 years and to lower required emission reductions. 15. [↵][47]US Environmental Protection Agency, “Control of Air Pollution From New Motor Vehicles: Heavy-Duty Engine Standards” [proposed rule]; [][48]. Acknowledgments: We thank K. Peterson (University of California, Berkeley) for data visualization; K. Karparos, C. Parmer, and B. Holmes-Gen (CARB) for manuscript review; M. Houyoux, J. Godfrey, and M. Aldrich (EPA) for assistance with NEI data; and J. Austin, R. Boyd, T. Brasil, J. Cao, M. Diaz, R. Furey, J. Herner, S. Huber, M. Komlenic, R. Krieger, T. Kuwayama, N. Lowery, N. Motallebi, S. Pournazeri, S. Yoon, S. Zelinka, and L. Zhou (CARB) for assistance with CARB regulations and data. This research was supported in part by California Breast Cancer Research Program grant 23QB-1881. J.B. serves as the Physician Member of CARB. A.A. is a former employee of CARB. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: pending:yes [10]: #ref-9 [11]: #ref-10 [12]: #ref-11 [13]: #ref-12 [14]: #ref-13 [15]: #ref-14 [16]: #ref-15 [17]: [18]: #xref-ref-1-1 "View reference 1 in text" [19]: {openurl}?query=rft.jtitle%253DLancet%26rft.volume%253D392%26rft.spage%253D1923%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0140-6736%252818%252932225-6%26rft_id%253Dinfo%253Apmid%252F30496105%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: /lookup/external-ref?access_num=10.1016/S0140-6736(18)32225-6&link_type=DOI [21]: /lookup/external-ref?access_num=30496105&link_type=MED&atom=%2Fsci%2F371%2F6536%2F1314.atom [22]: #xref-ref-2-1 "View reference 2 in text" [23]: [24]: #xref-ref-3-1 "View reference 3 in text" [25]: [26]: #xref-ref-4-1 "View reference 4 in text" [27]: [28]: #xref-ref-5-1 "View reference 5 in text" [29]: {openurl}?query=rft.jtitle%253DAnnu.%2BRev.%2BPublic%2BHealth%26rft.volume%253D41%26rft.spage%253D347%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [30]: #xref-ref-6-1 "View reference 6 in text" [31]: [32]: #xref-ref-7-1 "View reference 7 in text" [33]: [34]: #xref-ref-8-1 "View reference 8 in text" [35]: {openurl}?query=rft.jtitle%253DAtmos.%2BEnviron.%26rft.volume%253D107%26rft.spage%253D70%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [36]: #xref-ref-9-1 "View reference 9 in text" [37]: [38]: #xref-ref-10-1 "View reference 10 in text" [39]: #xref-ref-11-1 "View reference 11 in text" [40]: [41]: #xref-ref-12-1 "View reference 12 in text" [42]: [43]: #xref-ref-13-1 "View reference 13 in text" [44]: {openurl}?query=rft.jtitle%253DScience%2BAdvances%26rft.stitle%253DSci%2BAdv%26rft.aulast%253DWu%26rft.auinit1%253DX.%26rft.volume%253D6%26rft.issue%253D45%26rft.spage%253Deabd4049%26rft.epage%253Deabd4049%26rft.atitle%253DAir%2Bpollution%2Band%2BCOVID-19%2Bmortality%2Bin%2Bthe%2BUnited%2BStates%253A%2BStrengths%2Band%2Blimitations%2Bof%2Ban%2Becological%2Bregression%2Banalysis%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fsciadv.abd4049%26rft_id%253Dinfo%253Apmid%252F33148655%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6MzoiUERGIjtzOjExOiJqb3VybmFsQ29kZSI7czo4OiJhZHZhbmNlcyI7czo1OiJyZXNpZCI7czoxMzoiNi80NS9lYWJkNDA0OSI7czo0OiJhdG9tIjtzOjIzOiIvc2NpLzM3MS82NTM2LzEzMTQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [46]: #xref-ref-14-1 "View reference 14 in text" [47]: #xref-ref-15-1 "View reference 15 in text" [48]:

Deep science: AI is in the air, water, soil and steel – TechCrunch


Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect some of the most relevant recent discoveries and papers -- particularly in but not limited to artificial intelligence -- and explain why they matter. This week brings a few unusual applications of or developments in machine learning, as well as a particularly unusual rejection of the method for pandemic-related analysis. One hardly expects to find machine learning in the domain of government regulation, if only because one assumes federal regulators are hopelessly behind the times when it comes to this sort of thing. So it may surprise you that the U.S. Environmental Protection Agency has partnered with researchers at Stanford to algorithmically root out violators of environmental rules.

Assessing regulatory fairness through machine learning


The analysis, published this week in the proceedings of the Association of Computing Machinery Conference on Fairness, Accountability and Transparency(link is external), evaluates machine learning techniques designed to support a U.S. Environmental Protection Agency (EPA) initiative to reduce severe violations of the Clean Water Act. It reveals how two key elements of so-called algorithmic design influence which communities are targeted for compliance efforts and, consequently, who bears the burden of pollution violations. The analysis -- funded through the Stanford Woods Institute for the Environment's Realizing Environmental Innovation Program -- is timely given recent executive actions(link is external) calling for renewed focus on environmental justice. "Machine learning is being used to help manage an overwhelming number of things that federal agencies are tasked to do -- as a way to help increase efficiency," said study co-principal investigator Daniel Ho, the William Benjamin Scott and Luna M. Scott Professor of Law at Stanford Law School. "Yet what we also show is that simply designing a machine learning-based system can have an additional benefit."

EPA Kicks Off America Recycles Week with Second Annual Innovation Fair


This week, the U.S. Environmental Protection Agency (EPA) celebrates America Recycles Week by hosting two days of free, virtual events that focus on creating a more robust and sustainable recycling system in the U.S. and abroad. Today, the America Recycles: Innovation Fair will feature more than 40 innovators from across the recycling system via virtual exhibit halls demonstrating their state-of-the-art products, services, outreach, and technologies. They are advancing the recycling system through strategies such as: deploying artificial intelligence robots to enhance operations at recycling facilities; using hard-to-recycle plastics in 3D printing materials; installing small system sorting units in stadiums and small communities; creating new construction materials from hard-to-recycle plastics; and using automated technology and recycled glass bottles to create new glassware. "EPA is proud to showcase top recycling innovators at the virtual Innovation Fair today," said EPA Administrator Andrew Wheeler. "Tomorrow's America Recycles Summit will include EPA's announcement of the first National Recycling Goal, which will prompt a whole new level of dialogue among stakeholders on how to improve our domestic recycling infrastructure."

Can Artificial Intelligence Save the Regulatory State?


The Department of Justice recently sued Google for allegedly monopolizing the market for search engines. The Department's complaint alleges that Google took numerous actions well before 2010 that formed part of the claimed antitrust violations. I have no comment about the merits. What I do want to call attention to, however, are the dates: a lawsuit beginning in 2020 to try to correct the market consequences of actions that began more than 10 years ago. The revolution that some scholars call "regulating by robot" is already underway.

Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants Machine Learning

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. With the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our models using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

Distorting science, putting water at risk


The Navigable Waters Protection Rule (NWPR) ([ 1 ][1]), which was published in April by the U.S. Environmental Protection Agency (EPA) and the Department of the Army (“the Agencies”), has redefined “waters of the U.S.” (WOTUS) to restrict federal protection of vulnerable waters ([ 2 ][2]). With its emphasis on “continuous surface connections” and “permanen[ce],” the NWPR removes or reduces protection for U.S. waters, including millions of miles of streams and acres of wetlands, many of which comprise headwaters that are critical for sustaining water quality and healthy watersheds ([ 3 ][3]) (see the figure). Although the Agencies claim to have “looked to scientific principles to inform” the NWPR, science has been largely ignored and oversimplified. These new exclusions are based on selective parsing of statutory language and earlier case law, rather than on previously established, science-based interpretations of the U.S. Federal Water Pollution Control Act, commonly known as the Clean Water Act (CWA) ([ 4 ][4]). The EPA's own Science Advisory Board (SAB) found sufficient evidence to conclude that “…the proposed Rule lacks a scientific justification, while potentially introducing new risks to human and environmental health” ([ 5 ][5]). Responding to this unprecedented distortion of science and rollback in water protections, which went into effect nationwide on 22 June, will require coordinated efforts among scientists, lawmakers, and resource managers. Clearly articulated in the CWA is the intention “to restore and maintain the chemical, physical, and biological integrity of the Nation's waters” ([ 4 ][4]). The CWA was explicit in protecting “navigable waters,” which Congress defined broadly as WOTUS; however, the extent to which waters other than navigable rivers, lakes, and territorial seas [traditional navigable waters (TNWs)] are protected has repeatedly provoked legal skirmishing. Particularly contentious are determinations about which nontraditional waters, such as wetlands and small tributary streams, contribute to the integrity of TNWs. The NWPR functionally ends the debate by elevating state over federal regulatory authority. Without federal law as a protective regulatory floor, states can and often do choose to leave waterbodies unprotected, making waters vulnerable to unregulated pollution, dredging, filling, and other activities that may profoundly erode water quality ([ 3 ][3]). The NWPR downplays science by redefining protected “waters” and explicitly states that “science cannot dictate where to draw the line between Federal and State waters.” The NWPR relies overwhelmingly (and arguably arbitrarily) upon the 2006 Supreme Court opinion by Justice Scalia in Rapanos v. United States, Carabell v. United States Army Corps of Engineers that lacked majority support. A more scientifically nuanced position was articulated by Justice Kennedy on the same case; the four dissenting Justices agreed with Kennedy's rationales for protecting waters, but would have protected even more. The realized impacts are likely to be worse than projected, as ephemeral streams and nonfloodplain wetlands are usually underestimated by remotely sensed data ([ 3 ][3]). The economic analysis filed with the NWPR was largely silent about impacts, simply acknowledging that “the [A]gencies are unable to quantify [the scope] of these changes with any reliable accuracy” owing to geospatial data issues and uncertainty about government responses ([ 6 ][6]). Yet, in spite of this uncertainty and the potential for harm, the Agencies proceeded with a restrictive and risky rule. Connectivity is a cornerstone in understanding how freshwater ecosystem functions are sustained. In 2015, the Obama administration promulgated the Clean Water Rule (CWR) that included all tributaries and most wetlands as WOTUS ([ 7 ][7]). The scientific rationale for the CWR was reviewed in the EPA Connectivity Report ([ 8 ][8]), which synthesized >1200 peer-reviewed scientific publications and input from 49 technical experts. After a public review process, the 25-member EPA SAB confirmed the scientific underpinnings of both the Connectivity Report and the CWR. Since then, the body of supporting evidence has grown ([ 3 ][3], [ 9 ][9]), enhancing our understanding of how the integrity of freshwater ecosystems within a watershed relates to the biological, chemical, and hydrological connectivity among waterbodies, including wetlands and ephemeral streams. This understanding recognizes as critical to services derived from freshwater ecosystems gradients of connectivity (versus a binary property: connected, not connected) that operate as a function of frequency, magnitude, timing, and duration of biological, chemical, and physical connections among waterbodies ([ 10 ][10]). By disregarding or misinterpreting the science of waterbody connectivity, the NWPR draws scientifically unsupported boundaries to distinguish WOTUS, reaches conclusions contrary to current science, and asserts legal and scientific views substantially different from those of the Agencies under previous administrations of both political parties going back to the 1970s. The NWPR promotes regulations contrary to what science shows about effective water protection. Although agencies often have latitude to adjust regulatory choices when implementing longstanding statutes, they cannot do so arbitrarily and without reasoned justification and rationales in light of relevant law, facts, and science. In contrast to the CWR's recognition of biological, chemical, and physical connectivity, the NWPR relies solely on direct hydrologic surface connectivity to determine wetland jurisdiction. Nonfloodplain wetlands and ephemeral streams are categorically excluded on the basis of lack of hydrological connectivity irrespective of their degree of biological or chemical connectivity. Also excluded are floodplain wetlands lacking a direct surface water connection to TNWs “in a typical year,” and intermittent tributaries lacking relatively permanent surface flows. Such exclusions are inconsistent with evidence demonstrating that these waters are functionally connected to and support the integrity of downstream waters. Removal of federal protection is likely to diminish numerous ecosystem services, such as safeguarding water quality and quantity, reducing or mitigating flood risk, conserving biodiversity, and maintaining recreationally and commercially valuable fisheries ([ 3 ][3]). Just as tiny capillaries play critical roles in the human body, nonfloodplain wetlands (so-called “isolated”) and ephemeral streams (that flow only after precipitation events) support an extensive suite of ecosystem services. Because nonfloodplain wetlands and ephemeral streams are connected to one another and downstream waters along a gradient of connectivity, they also provide substantial cumulative or aggregate ecosystem services ([ 10 ][10]). Because these wetlands and streams will summarily lose federal protection, they will be vulnerable to outright destruction, fill, or unpermitted industrial pollution discharges that risk transporting pollutants throughout watersheds. Losses of nonfloodplain wetlands could include particularly vulnerable and often valuable waters ([ 2 ][2]), including some playa lakes, prairie potholes, Carolina and Delmarva Bays, pocosins, and vernal pools. A preliminary analysis predicts widespread losses of wetland functions, with particularly high impacts on wetlands in arid and semi-arid regions. For example, the CWR protected 72%, whereas the NWPR will only protect 28% of wetland acres, in New Mexico's Río Peñasco watershed ([ 11 ][11]). The NWPR also categorically excludes subsurface hydrologic connectivity. To disregard groundwater connectivity is to disregard the scientific understanding of how natural waters function. The Agencies justify this exclusion by claiming that “A groundwater or subsurface connection could also be confusing and difficult to implement.” Although implementation may be challenging in some cases, claimed implementation ease under the NWPR should not supersede an evidence-based determination of connectivity given the potential for economic and environmental harm. The NWPR directly conflicts with a growing body of scientific evidence and with input and review by federal and nonfederal scientists. The rule narrows WOTUS in ways that are inconsistent with longstanding views about the CWA's mandate to safeguard access to clean water. The NWPR opens previously protected waters to filling, impairment, and industrial pollution, and will undermine decades of investments restoring water quality across the United States and lead to profound loss or impairment of ecosystems and the services they provide. For context, the economic value of ecosystem services provisioned by nonfloodplain wetlands alone has been estimated at $673 billion per year ([ 2 ][2]). Congress has the power to strengthen the CWA by enacting new legislation to replace or repeal the NWPR. Future administrations can reassess and act to restore protections through new rulemaking, without the need for new legislation. Toward these ends, the scientific community has already spoken on the matter, proposing three frameworks for the development of renewed protections based on sound scientific merits ([ 2 ][2]). Meanwhile, litigation may present challenges to and perhaps enjoin implementation of the NWPR. The April 2020 County of Maui v. Hawaii Wildlife Fund may help. In that case, the U.S. Supreme Court rejected an argument that would have eliminated federal CWA protections. The Court instead called for a functional and context-sensitive analysis of the disputed activities and their effects to determine federal jurisdiction over intentional pollution discharges into groundwater that predictably flows into WOTUS. In that 6 to 3 decision, the Court laid out a clear scientific basis for closing a loophole in the CWA, affirming for the first time that pollutants that travel through groundwater and then emerge into surface waters are in fact covered by the CWA. ![Figure][12] Protected versus unprotected waters Multiple waterbody types were initially under consideration for protection as “waters of the United States” under the Navigable Waters Protection Rule. Ephemeral streams flow only after precipitation events, intermittent streams flow periodically or seasonally, and perennial streams flow continuously. There are many types of nonfloodplain, or “isolated” wetlands, including prairie potholes and vernal pools, as illustrated here. GRAPHIC: MELISSA THOMAS BAUM/ SCIENCE Redoubled research efforts also can help address knowledge gaps critical for effective water policy. Quantifying the potential “harm” to clean water that will be caused by the NWPR is critical for both litigation and future rulemaking. Thus, the scientific community will be challenged to further demonstrate the consequences of changes to physical, chemical, and biological connectivity on water quality—especially in the context of nonperennial streams and nonfloodplain wetlands. Research-based evidence on the impacts of climate change were notably absent in the NWPR and will also be critical in challenging the rule. Under current human-use and water-management schemes, many stream flows are declining, such that intermittent and perennial streams are increasingly being replaced with ephemeral streams that will lose protection. For example, the Upper Kansas River Basin lost 558 km (21%) of stream length between 1950 and 1980, presumably as a result of groundwater pumping exacerbated by climate change, with a cumulative loss of 844 km (32%) predicted by 2060 ([ 12 ][13]). Reduced mountain snowpack and increased evaporation have been implicated in the ∼20% decline in the Colorado River's mean annual flow in comparison to the previous century; the Upper Colorado River basin supplies water to around 40 million people and supports ∼16 million jobs ([ 13 ][14]). Adoption of the NWPR is an indicator that the federal government is at least in part shedding the use of science and responsibility for water protection. Additional federal rollbacks of environmental protection, such as the Update to the Regulations Implementing the Procedural Provisions of the National Environmental Policy Act, a rule finalized on 15 July, could create a perfect storm for exploitation of water resources. Although federal statutes grant latitude to state, tribal, and local governments to provide additional, more protective regulation, many states do not do so, and many even prohibit regulations more stringent than federally required ([ 2 ][2], [ 14 ][15]). Thus, absent federal protections, many waterbodies will go unprotected. If the NWPR remains in place, local and grassroots approaches to water conservation, including watershed councils and coalitions, information and educational plans to reduce pollution, and university extension programs, will need to further mobilize to fill the vacuum created by the new rule. Such efforts would require additional resources and heightened stakeholder coordination. 1. [↵][16]U.S. Environmental Protection Agency and Department of Defense, Department of the Army, Corps of Engineers, The Navigable Waters Protection Rule: Definition of “Waters of the United States,” 85 Fed. Reg. 22250 (A2020). 2. [↵][17]1. I. F. Creed et al ., Nat. Geosci. 10, 809 (2017). [OpenUrl][18] 3. [↵][19]1. S. A R. Colvin et al ., Fisheries (Bethesda, MD) 44, 73 (2019). [OpenUrl][20][GeoRef][21] 4. [↵][22]Federal Water Pollution Control Act, 33 U.S.C. 1251 et seq., Sec. 101, p. 3 (1972). 5. [↵][23]U.S. EPA, Letter to Andrew Wheeler, 27 February 2020, SAB commentary on the proposed rule defining the scope of waters federally regulated under the Clean Water Act, EPA-SAB-20-002 (Environmental Protection Agency, 2020). 6. [↵][24]U.S. Environmental Protection Agency and Department of the Army, Economic analysis for the Navigable Waters Protection Rule: Definition of “Waters of the United States” (EPA, 2020). 7. [↵][25]U.S. Environmental Protection Agency and Department of Defense, Department of the Army, Corps of Engineers, Clean Water Rule: Definition of “Waters of the United States” 80 Fed. Reg. 37054 (EPA, 2015). 8. [↵][26]U.S. Environmental Protection Agency, Connectivity of streams and wetlands to downstream waters: a review and synthesis of the scientific evidence technical report, EPA/600/R-14/475F (EPA, 2015). 9. [↵][27]1. S. M. P. Sullivan, 2. M. C. Rains, 3. A. D. Rodewald , Proc. Natl. Acad. Sci. U.S.A. 116, 11558 (2019). [OpenUrl][28][FREE Full Text][29] 10. [↵][30]U.S. Environmental Protection Agency, Letter to Gina McCarthy, 17 October 2014. SAB review of the draft EPA report Connectivity of streams and wetlands to downstream waters: A review and synthesis of the scientific evidence (EPA, 2014). 11. [↵][31]1. R. Meyer, 2. A. Robertson , Navigable Waters Protection Rule spatial analysis: A GIS based scenario model for comparative analysis of the potential spatial extent of jurisdictional and non-jurisdictional waters and wetlands (Saint Mary's University of Minnesota, Winona, MN, 2020). 12. [↵][32]1. J. S. Perkin et al ., Proc. Natl. Acad. Sci. U.S.A. 114, 7373 (2017). [OpenUrl][33][Abstract/FREE Full Text][34] 13. [↵][35]1. P. C. D. Milly, 2. K. A. Dunne , Science 367, 1252 (2020). [OpenUrl][36][Abstract/FREE Full Text][37] 14. [↵][38]State constraints: State-imposed limitations on the authority of agencies to regulate waters beyond the scope of the federal Clean Water Act (Environmental Law Institute, 2013). Acknowledgments: We thank the many individuals who contributed to previous and related documents concerning the proposed replacement rule that helped inform this paper, including letters to the Federal Register (Docket ID No. EPAHQ-OW-2018-0149) and Public Input on the SAB Commentary on the Proposed Rule Defining the Scope of Waters Federally Regulated under the Clean Water Act (84 FR 4154). We also thank L. Poff, W. Kleindl, and three anonymous reviewers for their critiques and suggestions in earlier drafts. R. B. Keast and S.M.P.S. developed the figure. S.M.P.S. is currently providing advisory and expert consulting services to ongoing litigation regarding the NWPR. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: #ref-10 [11]: #ref-11 [12]: pending:yes [13]: #ref-12 [14]: #ref-13 [15]: #ref-14 [16]: #xref-ref-1-1 "View reference 1 in text" [17]: #xref-ref-2-1 "View reference 2 in text" [18]: {openurl}?query=rft.jtitle%253DNat.%2BGeosci.%26rft.volume%253D44%26rft.spage%253D73%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [19]: #xref-ref-3-1 "View reference 3 in text" [20]: {openurl}?query=rft.jtitle%253DFisheries%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [21]: /lookup/external-ref?access_num=1998000758&link_type=GEOREF [22]: #xref-ref-4-1 "View reference 4 in text" [23]: #xref-ref-5-1 "View reference 5 in text" [24]: #xref-ref-6-1 "View reference 6 in text" [25]: #xref-ref-7-1 "View reference 7 in text" [26]: #xref-ref-8-1 "View reference 8 in text" [27]: #xref-ref-9-1 "View reference 9 in text" [28]: {openurl}?query=rft.jtitle%253DProc.%2BNatl.%2BAcad.%2BSci.%2BU.S.A.%26rft_id%253Dinfo%253Adoi%252F10.1073%252Fpnas.1907489116%26rft_id%253Dinfo%253Apmid%252F31186378%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [29]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMjoiMTE2LzI0LzExNTU4IjtzOjQ6ImF0b20iO3M6MjI6Ii9zY2kvMzY5LzY1MDUvNzY2LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [30]: #xref-ref-10-1 "View reference 10 in text" [31]: #xref-ref-11-1 "View reference 11 in text" [32]: #xref-ref-12-1 "View reference 12 in text" [33]: {openurl}?query=rft.jtitle%253DProc.%2BNatl.%2BAcad.%2BSci.%2BU.S.A.%26rft_id%253Dinfo%253Adoi%252F10.1073%252Fpnas.1618936114%26rft_id%253Dinfo%253Apmid%252F28652354%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [34]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMToiMTE0LzI4LzczNzMiO3M6NDoiYXRvbSI7czoyMjoiL3NjaS8zNjkvNjUwNS83NjYuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [35]: #xref-ref-13-1 "View reference 13 in text" [36]: {openurl}?query=rft.jtitle%253DScience%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.aay9187%26rft_id%253Dinfo%253Apmid%252F32079679%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [37]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEzOiIzNjcvNjQ4My8xMjUyIjtzOjQ6ImF0b20iO3M6MjI6Ii9zY2kvMzY5LzY1MDUvNzY2LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [38]: #xref-ref-14-1 "View reference 14 in text"

Engage with animal welfare in conservation


Leading conservationists have emphasized that conservation's priority is the protection of species and populations, not the welfare of individual nonhuman animals (hereafter “animals”) ([ 1 ][1]–[ 3 ][2]). Although individual conservationists often harbor concern for animal welfare, conservation organizations and scientists frequently downplay or ignore the ethical implications of actions they promote that harm individual animals, from culling and sport hunting to the discontinuation of wildlife rescue from oil spills ([ 3 ][2]–[ 5 ][3]). A growing body of scientific evidence should prompt conservation organizations to reconsider their inattention to animal welfare. A wide variety of vertebrate species (and perhaps some invertebrates) are capable of experiencing physical and emotional pain, engaging in substantive relationships, and executing cognitively complex tasks ([ 6 ][4]–[ 8 ][5]), bolstering claims that animal well-being is morally significant and policy-relevant. Addressing animal welfare in conservation would be politically challenging, and given the central role of predation and competition in ecosystems, conservation science cannot altogether avoid difficult decisions; harming animals can be a necessary step toward a worthwhile goal. Despite these trade-offs, conservation organizations face a singular opportunity to reshape conservation into a discipline that promotes both the quantity of species and the quality of animal life. Although humans are exceptional in many ways, the once-popular belief that it is unscientific to ascribe emotions or thoughts to animals is now regarded as inconsistent with evolutionary theory, experimental evidence, and any reasonable burden of proof ([ 9 ][6], [ 10 ][7]). Commonalities in basic neural functioning across vertebrate species, ranging from fish to mammals, suggest similarities in experiential capacities ([ 9 ][6], [ 11 ][8]). Evidence indicates that the thalamocingulate division of the limbic system and the anterior cingulate cortex evolved prior to the radiation of mammals, with all studied mammals sharing seven basic emotional systems including joy, fear, grief, parental nurturance, and playfulness. Deep neurological similarities underpin the extensive use of mammalian models in medical research, including for depression and anxiety. Further, research indicates that convergent evolution of the mammalian cortex and avian pallium has led to similar neural architecture between birds and mammals ([ 12 ][9]), with birds exhibiting similar forms of some affective states, consciousness, and attachment-oriented behaviors. Recent research has also demonstrated that various animal species are cognitively sophisticated, with findings including tool use in diverse taxa; spontaneous insight and innovative behavior; self-recognition and metacognition; collaboration to solve unfamiliar tasks; planning for future events; political strategy; empathetic concern; and the ability to recognize hundreds of human words (see supplementary materials). The accumulating scientific evidence that animals have vibrant inner lives was anticipated by modern philosophers, the field of animal welfare science, and numerous world cultures that have accorded moral relevance to the quality of animal life. Yet with limited exceptions, the most prominent international conservation organizations do not attempt to promote animal welfare in their mission or vision statements or to safeguard animal welfare in their readily available public policies. This contrasts with often robust ethics policies on a range of other social and environmental issues. From one perspective, the omission of animal welfare is befuddling. Conservationists must believe that animals deserve protection from human-induced harm; by combating habitat destruction and poaching, conservation often already promotes wild animal welfare. Officially recognizing the imperative of protecting animals as individuals could broaden conservation's constituency. Whereas the public often finds the value of biodiversity to be abstract and unrelatable, many people are concerned when human actions unnecessarily violate the freedom and well-being of wild animals. Conservation organizations have realized this, often using stories of human-induced suffering of individual animals to generate empathy and raise funds. Yet, owing to the pervasiveness of activities that compromise animal welfare, many conservation organizations could face a variety of political risks and programmatic complications if they were to officially endorse the legitimacy of animal welfare concerns. Conservation organizations often depend on a diverse coalition of political interests, including groups that habitually harm animals. For instance, the U.S. government is one of the largest bilateral sources of funding for international conservation largely because the U.S. Congress's International Conservation Caucus is among the largest bipartisan caucuses in the legislature, with many participants being vocal supporters of recreational hunting and fishing. For conservation organizations to acknowledge that killing animals for recreation might have moral implications ([ 4 ][10]) could complicate these politically important relationships in both halls of power and remote settings globally. There are well-evidenced concerns for how wild animals, especially wide-ranging species like elephants, some cetaceans, and carnivores, fare in captivity, but zoos can also inspire considerable support for wildlife conservation. Finally, conservation organizations and conservationists themselves (like other environmentalists) often regularly purchase factory farm products even though factory farms pose serious concerns about human-induced animal suffering. For conservation organizations, officially acknowledging the moral significance of animal welfare could complicate how many conservationists see themselves and generally cause discontent within their communities. Furthermore, conservation programming takes place in complex socioecological systems that pose practical trade-offs between animal welfare and biodiversity conservation or even human rights. At its extreme, efforts to curtail hunting and fishing in the world's poor rural areas could unjustly harm communities that rely on bushmeat or wild fish for their nutrition and livelihoods. Conservation groups can be seen as elitist, out-of-touch, or culturally oppressive where they oppose the killing of dangerous animals like elephants or traditional practices like subsistence whaling—such conflicts could become more common if conservation organizations consistently prioritize the interests of individual animals. In settings where wildlife tourism is not profitable, prohibiting sport hunting could deprive organizations of funding to protect wildlife from poaching, perversely leading to an increase in the killing of wildlife. Additionally, there are many examples of direct trade-offs between animal welfare and traditional conservation objectives like preventing extinction and maintaining ecosystem function. Invasive mammals—like goats on the Galapagos or feral cats on remote islands—suffer during eradication campaigns, but there may be no other way to secure the future for endangered native species. Programs to cull white-tailed deer similarly might be necessary to ensure the regeneration of forests in the eastern United States. Ecological research and reintroduction programs can also involve duress for the animals involved. Despite challenges posed by these trade-offs, conservation science should adjust its priorities in response to the overwhelming evidence that animals think and feel. Only explicit consideration of animal welfare in decision-making can ensure that conservation organizations do not unnecessarily compromise the well-being of individual animals. As a community, conservation organizations should set in motion three processes to (i) develop consensus principles, (ii) build the evidence base to identify best practices, and (iii) develop advisory institutions that can advance best practices. Each of these should engage diverse voices, including representatives from different cultures, countries with diverse political realities, and researchers and practitioners from both animal welfare science and conservation. The process of developing consensus principles to bring animal welfare concerns into conservation science has already begun, with ideas coming from national regulatory bodies, nongovernmental organizations concerned with wild animal welfare, the World Association of Zoos and Aquariums ([ 13 ][11]), animal welfare experts ([ 14 ][12], [ 15 ][13]), and the burgeoning compassionate conservation movement ([ 3 ][2], [ 4 ][10]). Conservation and animal welfare organizations should collaborate to systematically refine and select practically applicable ethical principles. Given the diverse cultural practices and economic systems that involve harm to animals, prohibitions on animal captivity, killing animals, and eating meat are unlikely to gain consensus support—but that need not prevent constructive discussions on minimizing human-induced suffering of animals, general agreement to minimize suffering during killing, and principles guiding the circumstances when killing animals might be acceptable. Animal welfare principles can alert conservationists to when the harm an activity causes to individual animals outweighs the benefits to biodiversity. Second, international conservation and animal welfare organizations should fund the development of an evidence base for how best to engage with wildlife in a way that minimizes avoidable suffering. Again, scientists have begun this process ([ 4 ][10], [ 13 ][11], [ 14 ][12])—but the evidence compiled must come from more diverse settings and situations and reflect practical limitations and trade-offs faced by conservation organizations in places where even human rights are not adequately realized. In addition to improving conservation practice, such evidence would help animal welfare organizations recognize where the protection of biodiversity, ecological function, and local communities might necessitate harming individual animals. This evidence review process would also highlight areas of research that could help resolve ethical dilemmas posed by conservation programming. International conservation bodies should also work with animal welfare scientists to establish advisory committees that review (voluntarily submitted) conservation project proposals to assess whether they satisfy principles of animal welfare. The process could be modeled as a voluntary version of the Institutional Animal Care and Use Committee that reviews animal research in the United States, working to promote best practices, build precedent, and collect real-life cases that can improve the evidence base. The committees' recommendations should provide a basis for informed debate about the trade-offs between wildlife conservation and animal welfare, helping better define whether the suffering of individual animals might be commensurate with conservation benefits ([ 14 ][12]). Over time, the cumulative experience of these committees should allow conservation organizations to recommend evidence-based animal welfare safeguards that can fit into the broader category of social and environmental safeguards, much like policies striving to minimize carbon emissions or protect human rights in conservation and development. Inevitably, these processes will take time. In the meanwhile, conservation organizations can take two steps toward building a better world for all animals: publicly commit to considering animal welfare in their decisions, and adopt policies against the purchase of factory farm meat where less harmful alternatives are available. Given the implications of factory farming not just for animal welfare but also for climate change and biodiversity, such action would further demonstrate the sincerity of conservation organizations' pursuit of a more just and sustainable planet. [][14] 1. [↵][15]1. M. E. Soule , Bioscience 35, 727 (1985). [OpenUrl][16][CrossRef][17][Web of Science][18] 2. 1. P. Kareiva, 2. M. Marvier , Bioscience 62, 962 (2012). [OpenUrl][19][CrossRef][20][Web of Science][21] 3. [↵][22]1. D. Ramp, 2. M. Bekoff , Bioscience 65, 323 (2015). [OpenUrl][23][CrossRef][24] 4. [↵][25]1. A. D. Wallach et al ., Conserv. Biol. 32, 1255 (2018). [OpenUrl][26] 5. [↵][27]1. P. Kareiva, 2. M. Marvier, 3. B. Silliman 1. J. A. Estes, 2. M. T. Tinker , in Effective Conservation Science: Data Not Dogma, P. Kareiva, M. Marvier, B. Silliman, Eds. (Oxford Univ. Press, 2017), pp. 128–134. 6. [↵][28]1. V. A. Braithwaite, 2. P. Boulcott , Dis. Aquat. Organ. 75, 131 (2007). [OpenUrl][29][PubMed][30] 7. 1. I. B.-A. Bartal et al ., Science 334, 1427 (2011). [OpenUrl][31][Abstract/FREE Full Text][32] 8. [↵][33]1. N. S. Clayton, 2. A. Dickinson , Nature 395, 272 (1998). [OpenUrl][34][CrossRef][35][PubMed][36][Web of Science][37] 9. [↵][38]1. J. Panksepp , PLOS ONE 6, e21236 (2011). [OpenUrl][39][CrossRef][40][PubMed][41] 10. [↵][42]1. G. A. Mashour, 2. M. T. Alkire , Proc. Natl. Acad. Sci. U.S.A. 110 (suppl.2), 10357 (2013). [OpenUrl][43][Abstract/FREE Full Text][44] 11. [↵][45]1. T. E. Feinberg, 2. J. Mallatt , Front. Psychol. 4, 667 (2013). [OpenUrl][46][PubMed][47] 12. [↵][48]1. A. B. Butler, 2. R. M. J. Cotterill , Biol. Bull. 211, 106 (2006). [OpenUrl][49][CrossRef][50][PubMed][51][Web of Science][52] 13. [↵][53]1. D. J. Mellor et al ., Caring for Wildlife: The World Zoo and Aquarium Animal Welfare Strategy (WAZA Executive Office, 2015). 14. [↵][54]1. S. Dubois et al ., Conserv. Biol. 31, 753 (2017). [OpenUrl][55] 15. [↵][56]1. J. O. Hampton et al ., Conserv. Biol. 33, 751 (2019). [OpenUrl][57] Acknowledgments: We thank H. Telkänranta, N. Shah, S. Sekar, N. Mohapatra, D. Mistree, M.Malik, A.Lerner, K. Kolappa, S. Kishore, P. Hannam, G. Fricchione, M. Doshi, P. Chanchani, and four anonymous reviewers. This piece reflects the views of the authors and not the official positions of their organizations. [1]: #ref-1 [2]: #ref-3 [3]: #ref-5 [4]: #ref-6 [5]: #ref-8 [6]: #ref-9 [7]: #ref-10 [8]: #ref-11 [9]: #ref-12 [10]: #ref-4 [11]: #ref-13 [12]: #ref-14 [13]: #ref-15 [14]: [15]: #xref-ref-1-1 "View reference 1 in text" [16]: {openurl}?query=rft.jtitle%253DBioscience%26rft_id%253Dinfo%253Adoi%252F10.2307%252F1310054%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [17]: /lookup/external-ref?access_num=10.2307/1310054&link_type=DOI [18]: /lookup/external-ref?access_num=A1985AUV2000010&link_type=ISI [19]: {openurl}?query=rft.jtitle%253DBioscience%26rft_id%253Dinfo%253Adoi%252F10.1525%252Fbio.2012.62.11.5%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: /lookup/external-ref?access_num=10.1525/bio.2012.62.11.5&link_type=DOI [21]: /lookup/external-ref?access_num=000311661000006&link_type=ISI [22]: #xref-ref-3-1 "View reference 3 in text" [23]: {openurl}?query=rft.jtitle%253DBioscience%26rft_id%253Dinfo%253Adoi%252F10.1093%252Fbiosci%252Fbiu223%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [24]: /lookup/external-ref?access_num=10.1093/biosci/biu223&link_type=DOI [25]: #xref-ref-4-1 "View reference 4 in text" [26]: {openurl}?query=rft.jtitle%253DConserv.%2BBiol.%26rft.volume%253D32%26rft.spage%253D1255%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [27]: #xref-ref-5-1 "View reference 5 in text" [28]: #xref-ref-6-1 "View reference 6 in text" [29]: {openurl}?query=rft.jtitle%253DDiseases%2Bof%2Baquatic%2Borganisms%26rft.stitle%253DDis%2BAquat%2BOrgan%26rft.aulast%253DBraithwaite%26rft.auinit1%253DV.%2BA.%26rft.volume%253D75%26rft.issue%253D2%26rft.spage%253D131%26rft.epage%253D138%26rft.atitle%253DPain%2Bperception%252C%2Baversion%2Band%2Bfear%2Bin%2Bfish.%26rft_id%253Dinfo%253Apmid%252F17578252%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [30]: /lookup/external-ref?access_num=17578252&link_type=MED&atom=%2Fsci%2F369%2F6504%2F629.atom [31]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DBartal%26rft.auinit1%253DI.%2BB.-A.%26rft.volume%253D334%26rft.issue%253D6061%26rft.spage%253D1427%26rft.epage%253D1430%26rft.atitle%253DEmpathy%2Band%2BPro-Social%2BBehavior%2Bin%2BRats%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.1210789%26rft_id%253Dinfo%253Apmid%252F22158823%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [32]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEzOiIzMzQvNjA2MS8xNDI3IjtzOjQ6ImF0b20iO3M6MjI6Ii9zY2kvMzY5LzY1MDQvNjI5LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [33]: #xref-ref-8-1 "View reference 8 in text" [34]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DClayton%26rft.auinit1%253DN.%2BS.%26rft.volume%253D395%26rft.issue%253D6699%26rft.spage%253D272%26rft.epage%253D274%26rft.atitle%253DEpisodic-like%2Bmemory%2Bduring%2Bcache%2Brecovery%2Bby%2Bscrub%2Bjays.%26rft_id%253Dinfo%253Adoi%252F10.1038%252F26216%26rft_id%253Dinfo%253Apmid%252F9751053%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [35]: /lookup/external-ref?access_num=10.1038/26216&link_type=DOI [36]: /lookup/external-ref?access_num=9751053&link_type=MED&atom=%2Fsci%2F369%2F6504%2F629.atom [37]: /lookup/external-ref?access_num=000075974600049&link_type=ISI [38]: #xref-ref-9-1 "View reference 9 in text" [39]: {openurl}?query=rft.stitle%253DPLoS%2BONE%26rft.aulast%253DPanksepp%26rft.auinit1%253DJ.%26rft.volume%253D6%26rft.issue%253D9%26rft.spage%253De21236%26rft.epage%253De21236%26rft.atitle%253DCross-species%2Baffective%2Bneuroscience%2Bdecoding%2Bof%2Bthe%2Bprimal%2Baffective%2Bexperiences%2Bof%2Bhumans%2Band%2Brelated%2Banimals.%26rft_id%253Dinfo%253Adoi%252F10.1371%252Fjournal.pone.0021236%26rft_id%253Dinfo%253Apmid%252F21915252%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [40]: /lookup/external-ref?access_num=10.1371/journal.pone.0021236&link_type=DOI [41]: /lookup/external-ref?access_num=21915252&link_type=MED&atom=%2Fsci%2F369%2F6504%2F629.atom [42]: #xref-ref-10-1 "View reference 10 in text" [43]: {openurl}?query=rft.jtitle%253DProc.%2BNatl.%2BAcad.%2BSci.%2BU.S.A.%26rft_id%253Dinfo%253Adoi%252F10.1073%252Fpnas.1301188110%26rft_id%253Dinfo%253Apmid%252F23754370%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [44]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoyMjoiMTEwL1N1cHBsZW1lbnRfMi8xMDM1NyI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM2OS82NTA0LzYyOS5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [45]: #xref-ref-11-1 "View reference 11 in text" [46]: {openurl}?query=rft.jtitle%253DFront.%2BPsychol.%26rft.volume%253D4%26rft.spage%253D667%26rft_id%253Dinfo%253Apmid%252F24109460%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [47]: /lookup/external-ref?access_num=24109460&link_type=MED&atom=%2Fsci%2F369%2F6504%2F629.atom [48]: #xref-ref-12-1 "View reference 12 in text" [49]: {openurl}?query=rft.jtitle%253DThe%2BBiological%2BBulletin%26rft.stitle%253DBiol.%2BBull.%26rft.aulast%253DButler%26rft.auinit1%253DA.%2BB.%26rft.volume%253D211%26rft.issue%253D2%26rft.spage%253D106%26rft.epage%253D127%26rft.atitle%253DMammalian%2Band%2Bavian%2Bneuroanatomy%2Band%2Bthe%2Bquestion%2Bof%2Bconsciousness%2Bin%2Bbirds.%26rft_id%253Dinfo%253Adoi%252F10.2307%252F4134586%26rft_id%253Dinfo%253Apmid%252F17062871%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [50]: /lookup/external-ref?access_num=10.2307/4134586&link_type=DOI [51]: /lookup/external-ref?access_num=17062871&link_type=MED&atom=%2Fsci%2F369%2F6504%2F629.atom [52]: /lookup/external-ref?access_num=000241793700003&link_type=ISI [53]: #xref-ref-13-1 "View reference 13 in text" [54]: #xref-ref-14-1 "View reference 14 in text" [55]: {openurl}?query=rft.jtitle%253DConserv.%2BBiol.%26rft.volume%253D31%26rft.spage%253D753%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [56]: #xref-ref-15-1 "View reference 15 in text" [57]: {openurl}?query=rft.jtitle%253DConserv.%2BBiol.%26rft.volume%253D33%26rft.spage%253D751%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx

NASEM Seeks Nominations for Experts for Committee on Anticipatory Research for EPA's ORD to Inform Future Environmental Protection


The National Academies of Sciences, Engineering, and Medicine (NASEM) are now assembling an ad hoc committee to identify emerging scientific and technological advances from across a broad range of disciplines that the U.S. Environmental Protection Agency's (EPA) Office of Research and Development (ORD) should consider in its research planning to support EPA's mission for protecting human health and the environment. In addition, according to NASEM, the committee will recommend how ORD could best take advantage of those advances to meet current and future challenges during the next 10 - 20 years. NASEM states that the committee will consider EPA's mission, strategic planning documents, and current initiatives, as well as other broader topics, including, but not limited to, biotechnology, big data, climate impacts, environmental monitoring and sensors, impacts of stressors on ecological and human health, and artificial intelligence and machine learning. The committee also will consider advances that help EPA better incorporate systems thinking into multimedia, multidisciplinary approaches. Nominations for committee members and reviewers are due August 5, 2020.

LexNLP: Natural language processing and information extraction for legal and regulatory texts


By accepting the Deed and closing the Transaction, Buyer, on behalf of itself and its successors and assigns, shall thereby release each of the Seller Parties from, and waive any and all Liabilities against each of the Seller Parties for, attributable to, or in connection with the Property, whether arising or accruing before, on or after the Closing and whether attributable to events or circumstances which arise or occur before, on or after the Closing, including, without limitation, the following: (a) any and all statements or opinions heretofore or hereafter made, or information furnished, by any Seller Parties to any Buyerâ s Representatives; and (b) any and all Liabilities with respect to the structural, physical, or environmental condition of the Property, including, without limitation, all Liabilities relating to the release, presence, discovery or removal of any hazardous or regulated substance, chemical, waste or material that may be located in, at, about or under the Property, or connected with or arising out of any and all claims or causes of action based upon CERCLA (Comprehensive Environmental Response, Compensation, and Liability Act of 1980, 42 U.S.C. Notwithstanding the foregoing, the foregoing release and waiver is not intended and shall not be construed as affecting or impairing any rights or remedies that Buyer may have against Seller with respect to (i) a breach of any of Sellerâ s Warranties, (ii) a breach of any Surviving Covenants, or (iii) any acts constituting fraud by Seller.